Overview

Dataset statistics

Number of variables62
Number of observations94
Missing cells2318
Missing cells (%)39.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.7 KiB
Average record size in memory497.4 B

Variable types

Numeric11
Categorical42
Unsupported9

Alerts

airdate has constant value "2020-12-22" Constant
_embedded.show.externals.tvrage has constant value "19056.0" Constant
_embedded.show.dvdCountry.name has constant value "Japan" Constant
_embedded.show.dvdCountry.code has constant value "JP" Constant
_embedded.show.dvdCountry.timezone has constant value "Asia/Tokyo" Constant
url has a high cardinality: 94 distinct values High cardinality
name has a high cardinality: 86 distinct values High cardinality
_links.self.href has a high cardinality: 94 distinct values High cardinality
_embedded.show.url has a high cardinality: 60 distinct values High cardinality
_embedded.show.name has a high cardinality: 60 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 51 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 57 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 57 distinct values High cardinality
_embedded.show.summary has a high cardinality: 54 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 60 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 60 distinct values High cardinality
id is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
number is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.updated is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 6 other fieldsHigh correlation
id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
season is highly correlated with number and 3 other fieldsHigh correlation
number is highly correlated with season and 5 other fieldsHigh correlation
runtime is highly correlated with season and 3 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.externals.thetvdb is highly correlated with number and 4 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 4 other fieldsHigh correlation
id is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
season is highly correlated with _embedded.show.externals.thetvdbHigh correlation
number is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 3 other fieldsHigh correlation
id is highly correlated with url and 34 other fieldsHigh correlation
url is highly correlated with id and 45 other fieldsHigh correlation
name is highly correlated with id and 41 other fieldsHigh correlation
season is highly correlated with url and 28 other fieldsHigh correlation
number is highly correlated with url and 27 other fieldsHigh correlation
type is highly correlated with url and 17 other fieldsHigh correlation
airtime is highly correlated with url and 38 other fieldsHigh correlation
airstamp is highly correlated with id and 39 other fieldsHigh correlation
runtime is highly correlated with id and 37 other fieldsHigh correlation
summary is highly correlated with id and 38 other fieldsHigh correlation
rating.average is highly correlated with url and 30 other fieldsHigh correlation
_links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.type is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.status is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.weight is highly correlated with url and 36 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with url and 36 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 33 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 45 other fieldsHigh correlation
image.medium is highly correlated with id and 44 other fieldsHigh correlation
image.original is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 30 other fieldsHigh correlation
number has 1 (1.1%) missing values Missing
runtime has 3 (3.2%) missing values Missing
image has 94 (100.0%) missing values Missing
summary has 80 (85.1%) missing values Missing
rating.average has 89 (94.7%) missing values Missing
_embedded.show.language has 1 (1.1%) missing values Missing
_embedded.show.runtime has 17 (18.1%) missing values Missing
_embedded.show.averageRuntime has 2 (2.1%) missing values Missing
_embedded.show.ended has 63 (67.0%) missing values Missing
_embedded.show.officialSite has 9 (9.6%) missing values Missing
_embedded.show.rating.average has 92 (97.9%) missing values Missing
_embedded.show.network has 94 (100.0%) missing values Missing
_embedded.show.webChannel.id has 2 (2.1%) missing values Missing
_embedded.show.webChannel.name has 2 (2.1%) missing values Missing
_embedded.show.webChannel.country has 94 (100.0%) missing values Missing
_embedded.show.webChannel.officialSite has 40 (42.6%) missing values Missing
_embedded.show.dvdCountry has 94 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 93 (98.9%) missing values Missing
_embedded.show.externals.thetvdb has 35 (37.2%) missing values Missing
_embedded.show.externals.imdb has 45 (47.9%) missing values Missing
_embedded.show.image.medium has 3 (3.2%) missing values Missing
_embedded.show.image.original has 3 (3.2%) missing values Missing
_embedded.show.summary has 7 (7.4%) missing values Missing
image.medium has 69 (73.4%) missing values Missing
image.original has 69 (73.4%) missing values Missing
_embedded.show.network.id has 89 (94.7%) missing values Missing
_embedded.show.network.name has 89 (94.7%) missing values Missing
_embedded.show.network.country.name has 89 (94.7%) missing values Missing
_embedded.show.network.country.code has 89 (94.7%) missing values Missing
_embedded.show.network.country.timezone has 89 (94.7%) missing values Missing
_embedded.show.network.officialSite has 94 (100.0%) missing values Missing
_embedded.show.webChannel.country.name has 41 (43.6%) missing values Missing
_embedded.show.webChannel.country.code has 41 (43.6%) missing values Missing
_embedded.show.webChannel.country.timezone has 41 (43.6%) missing values Missing
_embedded.show._links.nextepisode.href has 88 (93.6%) missing values Missing
_embedded.show.image has 94 (100.0%) missing values Missing
_embedded.show.webChannel has 94 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 93 (98.9%) missing values Missing
_embedded.show.dvdCountry.code has 93 (98.9%) missing values Missing
_embedded.show.dvdCountry.timezone has 93 (98.9%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.rating.average is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show.network.id is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:46:49.747020
Analysis finished2022-09-06 02:47:03.814157
Duration14.07 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2030034.053
Minimum1960499
Maximum2380808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:03.885958image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1960499
5-th percentile1976044.65
Q11988066.25
median1992331.5
Q32015888.75
95-th percentile2297275.75
Maximum2380808
Range420309
Interquartile range (IQR)27822.5

Descriptive statistics

Standard deviation95673.28376
Coefficient of variation (CV)0.04712890585
Kurtosis5.253386531
Mean2030034.053
Median Absolute Deviation (MAD)9094
Skewness2.474227344
Sum190823201
Variance9153377225
MonotonicityNot monotonic
2022-09-05T21:47:04.002053image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20077501
 
1.1%
19883021
 
1.1%
19926801
 
1.1%
19926791
 
1.1%
19926781
 
1.1%
19926771
 
1.1%
19926761
 
1.1%
19926751
 
1.1%
19926741
 
1.1%
19926731
 
1.1%
Other values (84)84
89.4%
ValueCountFrequency (%)
19604991
1.1%
19645681
1.1%
19680031
1.1%
19756461
1.1%
19760441
1.1%
19760451
1.1%
19761641
1.1%
19761651
1.1%
19761661
1.1%
19773301
1.1%
ValueCountFrequency (%)
23808081
1.1%
23799311
1.1%
23181101
1.1%
23151171
1.1%
23110201
1.1%
22898751
1.1%
22877881
1.1%
21972881
1.1%
21761391
1.1%
21650081
1.1%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size880.0 B
https://www.tvmaze.com/episodes/2007750/stand-up-autsajd-1x10-filipp-voronin-499-iz-5
 
1
https://www.tvmaze.com/episodes/1988302/nwa-shockwave-1x04-episode-4
 
1
https://www.tvmaze.com/episodes/1992680/rhyme-time-town-singalongs-1x09-bunny-bedtime-hey-diddle-diddle-humpty-row-row-rows-the-boat
 
1
https://www.tvmaze.com/episodes/1992679/rhyme-time-town-singalongs-1x08-the-teaspoon-dance-jaimes-bridge-has-fallen-down-the-happy-hyena
 
1
https://www.tvmaze.com/episodes/1992678/rhyme-time-town-singalongs-1x07-mary-marys-mango-cake-twinkle-twinkle-little-star-itsy-bitsys-water-spout
 
1
Other values (89)
89 

Length

Max length145
Median length117
Mean length85.78723404
Min length63

Characters and Unicode

Total characters8064
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2007750/stand-up-autsajd-1x10-filipp-voronin-499-iz-5
2nd rowhttps://www.tvmaze.com/episodes/2008030/lab-s-antonom-belaevym-2x09-gruppa-skryptonite
3rd rowhttps://www.tvmaze.com/episodes/1964568/core-sense-1x12-episode-12
4th rowhttps://www.tvmaze.com/episodes/2052511/wu-shen-zhu-zai-1x86-episode-86
5th rowhttps://www.tvmaze.com/episodes/1993656/7-days-of-romance-2x01-episode-1

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2007750/stand-up-autsajd-1x10-filipp-voronin-499-iz-51
 
1.1%
https://www.tvmaze.com/episodes/1988302/nwa-shockwave-1x04-episode-41
 
1.1%
https://www.tvmaze.com/episodes/1992680/rhyme-time-town-singalongs-1x09-bunny-bedtime-hey-diddle-diddle-humpty-row-row-rows-the-boat1
 
1.1%
https://www.tvmaze.com/episodes/1992679/rhyme-time-town-singalongs-1x08-the-teaspoon-dance-jaimes-bridge-has-fallen-down-the-happy-hyena1
 
1.1%
https://www.tvmaze.com/episodes/1992678/rhyme-time-town-singalongs-1x07-mary-marys-mango-cake-twinkle-twinkle-little-star-itsy-bitsys-water-spout1
 
1.1%
https://www.tvmaze.com/episodes/1992677/rhyme-time-town-singalongs-1x06-cow-jig-frere-jacques-itsy-bitsys-mosaic1
 
1.1%
https://www.tvmaze.com/episodes/1992676/rhyme-time-town-singalongs-1x05-jaimes-ride-and-see-hickory-dickory-dock-chuckleys-fruit-fest1
 
1.1%
https://www.tvmaze.com/episodes/1992675/rhyme-time-town-singalongs-1x04-humpty-goes-fishing-humpty-dumpty-sat-on-a-wall-humptys-snow-day1
 
1.1%
https://www.tvmaze.com/episodes/1992674/rhyme-time-town-singalongs-1x03-carnival-samba-the-itsy-bitsy-spider-shadow-puppets1
 
1.1%
https://www.tvmaze.com/episodes/1992673/rhyme-time-town-singalongs-1x02-granny-dumptys-garden-ms-macdonald-has-a-farm-jack-and-jills-boat-ride1
 
1.1%
Other values (84)84
89.4%

Length

2022-09-05T21:47:04.123768image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2007750/stand-up-autsajd-1x10-filipp-voronin-499-iz-51
 
1.1%
https://www.tvmaze.com/episodes/2071494/youths-in-the-breeze-1x24-full-time-sworn-enemy-081
 
1.1%
https://www.tvmaze.com/episodes/2052511/wu-shen-zhu-zai-1x86-episode-861
 
1.1%
https://www.tvmaze.com/episodes/1993656/7-days-of-romance-2x01-episode-11
 
1.1%
https://www.tvmaze.com/episodes/2096299/no-turning-back-romance-1x05-51
 
1.1%
https://www.tvmaze.com/episodes/2315117/sono-koi-mousukoshi-atatamemasuka-1x06-episode-61
 
1.1%
https://www.tvmaze.com/episodes/2068349/doomsday-awakening-2x01-episode-11
 
1.1%
https://www.tvmaze.com/episodes/2068351/doomsday-awakening-2x02-episode-21
 
1.1%
https://www.tvmaze.com/episodes/2005750/legend-of-yun-qian-1x03-episode-31
 
1.1%
https://www.tvmaze.com/episodes/2071493/youths-in-the-breeze-1x23-full-time-sworn-enemy-071
 
1.1%
Other values (84)84
89.4%

Most occurring characters

ValueCountFrequency (%)
-687
 
8.5%
e648
 
8.0%
s513
 
6.4%
t491
 
6.1%
/470
 
5.8%
o432
 
5.4%
a362
 
4.5%
w353
 
4.4%
i301
 
3.7%
m299
 
3.7%
Other values (30)3508
43.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5524
68.5%
Decimal Number1101
 
13.7%
Other Punctuation752
 
9.3%
Dash Punctuation687
 
8.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e648
11.7%
s513
 
9.3%
t491
 
8.9%
o432
 
7.8%
a362
 
6.6%
w353
 
6.4%
i301
 
5.4%
m299
 
5.4%
p273
 
4.9%
d259
 
4.7%
Other values (16)1593
28.8%
Decimal Number
ValueCountFrequency (%)
1236
21.4%
2175
15.9%
0158
14.4%
9143
13.0%
776
 
6.9%
873
 
6.6%
667
 
6.1%
361
 
5.5%
460
 
5.4%
552
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/470
62.5%
.188
 
25.0%
:94
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-687
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5524
68.5%
Common2540
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e648
11.7%
s513
 
9.3%
t491
 
8.9%
o432
 
7.8%
a362
 
6.6%
w353
 
6.4%
i301
 
5.4%
m299
 
5.4%
p273
 
4.9%
d259
 
4.7%
Other values (16)1593
28.8%
Common
ValueCountFrequency (%)
-687
27.0%
/470
18.5%
1236
 
9.3%
.188
 
7.4%
2175
 
6.9%
0158
 
6.2%
9143
 
5.6%
:94
 
3.7%
776
 
3.0%
873
 
2.9%
Other values (4)240
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII8064
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
-687
 
8.5%
e648
 
8.0%
s513
 
6.4%
t491
 
6.1%
/470
 
5.8%
o432
 
5.4%
a362
 
4.5%
w353
 
4.4%
i301
 
3.7%
m299
 
3.7%
Other values (30)3508
43.5%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct86
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size880.0 B
Episode 1
 
4
Episode 15
 
3
Episode 16
 
3
Episode 54
 
2
Филипп Воронин "4,99 из 5"
 
1
Other values (81)
81 

Length

Max length79
Median length64
Mean length23.11702128
Min length1

Characters and Unicode

Total characters2173
Distinct characters107
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)87.2%

Sample

1st rowФилипп Воронин "4,99 из 5"
2nd rowGruppa Skryptonite
3rd rowEpisode 12
4th rowEpisode 86
5th rowEpisode 1

Common Values

ValueCountFrequency (%)
Episode 14
 
4.3%
Episode 153
 
3.2%
Episode 163
 
3.2%
Episode 542
 
2.1%
Филипп Воронин "4,99 из 5"1
 
1.1%
See Saw Mumpty Daw / Mary Mary Quite Contrary / Mary Mary's Hiking Trip1
 
1.1%
Mary Mary's Mango Cake / Twinkle Twinkle Little Star / Itsy Bitsy's Water Spout1
 
1.1%
Cow Jig / Frère Jacques / Itsy Bitsy's Mosaic1
 
1.1%
Jaime's Ride and See / Hickory Dickory Dock / Chuckley's Fruit Fest1
 
1.1%
Humpty Goes Fishing / Humpty Dumpty Sat on a Wall / Humpty's Snow Day1
 
1.1%
Other values (76)76
80.9%

Length

2022-09-05T21:47:04.243517image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode30
 
7.4%
24
 
5.9%
the8
 
2.0%
15
 
1.2%
20204
 
1.0%
154
 
1.0%
you4
 
1.0%
mary4
 
1.0%
and4
 
1.0%
23
 
0.7%
Other values (271)318
77.9%

Most occurring characters

ValueCountFrequency (%)
314
 
14.5%
e159
 
7.3%
a139
 
6.4%
o117
 
5.4%
i110
 
5.1%
s105
 
4.8%
t85
 
3.9%
n77
 
3.5%
r71
 
3.3%
d68
 
3.1%
Other values (97)928
42.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1354
62.3%
Uppercase Letter315
 
14.5%
Space Separator314
 
14.5%
Decimal Number101
 
4.6%
Other Punctuation61
 
2.8%
Other Letter18
 
0.8%
Dash Punctuation6
 
0.3%
Math Symbol2
 
0.1%
Close Punctuation1
 
< 0.1%
Open Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e159
11.7%
a139
 
10.3%
o117
 
8.6%
i110
 
8.1%
s105
 
7.8%
t85
 
6.3%
n77
 
5.7%
r71
 
5.2%
d68
 
5.0%
p66
 
4.9%
Other values (29)357
26.4%
Uppercase Letter
ValueCountFrequency (%)
E38
 
12.1%
S30
 
9.5%
M27
 
8.6%
T24
 
7.6%
D20
 
6.3%
R17
 
5.4%
B16
 
5.1%
F14
 
4.4%
H14
 
4.4%
C12
 
3.8%
Other values (19)103
32.7%
Other Letter
ValueCountFrequency (%)
و3
16.7%
م2
 
11.1%
1
 
5.6%
1
 
5.6%
د1
 
5.6%
ر1
 
5.6%
گ1
 
5.6%
س1
 
5.6%
ی1
 
5.6%
ز1
 
5.6%
Other values (5)5
27.8%
Decimal Number
ValueCountFrequency (%)
223
22.8%
120
19.8%
311
10.9%
410
9.9%
010
9.9%
510
9.9%
68
 
7.9%
83
 
3.0%
73
 
3.0%
93
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/20
32.8%
'12
19.7%
.9
14.8%
,7
 
11.5%
!4
 
6.6%
?4
 
6.6%
#2
 
3.3%
"2
 
3.3%
&1
 
1.6%
Space Separator
ValueCountFrequency (%)
314
100.0%
Dash Punctuation
ValueCountFrequency (%)
-6
100.0%
Math Symbol
ValueCountFrequency (%)
×2
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1643
75.6%
Common486
 
22.4%
Cyrillic26
 
1.2%
Arabic14
 
0.6%
Han4
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e159
 
9.7%
a139
 
8.5%
o117
 
7.1%
i110
 
6.7%
s105
 
6.4%
t85
 
5.2%
n77
 
4.7%
r71
 
4.3%
d68
 
4.1%
p66
 
4.0%
Other values (42)646
39.3%
Common
ValueCountFrequency (%)
314
64.6%
223
 
4.7%
/20
 
4.1%
120
 
4.1%
'12
 
2.5%
311
 
2.3%
410
 
2.1%
010
 
2.1%
510
 
2.1%
.9
 
1.9%
Other values (14)47
 
9.7%
Cyrillic
ValueCountFrequency (%)
и5
19.2%
а2
 
7.7%
з2
 
7.7%
о2
 
7.7%
р2
 
7.7%
н2
 
7.7%
п2
 
7.7%
в1
 
3.8%
М1
 
3.8%
ф1
 
3.8%
Other values (6)6
23.1%
Arabic
ValueCountFrequency (%)
و3
21.4%
م2
14.3%
د1
 
7.1%
ر1
 
7.1%
گ1
 
7.1%
س1
 
7.1%
ی1
 
7.1%
ز1
 
7.1%
ا1
 
7.1%
ب1
 
7.1%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2123
97.7%
Cyrillic26
 
1.2%
Arabic14
 
0.6%
None6
 
0.3%
CJK4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
314
 
14.8%
e159
 
7.5%
a139
 
6.5%
o117
 
5.5%
i110
 
5.2%
s105
 
4.9%
t85
 
4.0%
n77
 
3.6%
r71
 
3.3%
d68
 
3.2%
Other values (62)878
41.4%
Cyrillic
ValueCountFrequency (%)
и5
19.2%
а2
 
7.7%
з2
 
7.7%
о2
 
7.7%
р2
 
7.7%
н2
 
7.7%
п2
 
7.7%
в1
 
3.8%
М1
 
3.8%
ф1
 
3.8%
Other values (6)6
23.1%
Arabic
ValueCountFrequency (%)
و3
21.4%
م2
14.3%
د1
 
7.1%
ر1
 
7.1%
گ1
 
7.1%
س1
 
7.1%
ی1
 
7.1%
ز1
 
7.1%
ا1
 
7.1%
ب1
 
7.1%
None
ValueCountFrequency (%)
×2
33.3%
è2
33.3%
é1
16.7%
â1
16.7%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean238.4361702
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:04.336657image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation652.0637471
Coefficient of variation (CV)2.734751806
Kurtosis3.94749386
Mean238.4361702
Median Absolute Deviation (MAD)0
Skewness2.421475079
Sum22413
Variance425187.1303
MonotonicityNot monotonic
2022-09-05T21:47:04.420744image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
154
57.4%
218
 
19.1%
202011
 
11.7%
34
 
4.3%
43
 
3.2%
231
 
1.1%
181
 
1.1%
71
 
1.1%
311
 
1.1%
ValueCountFrequency (%)
154
57.4%
218
 
19.1%
34
 
4.3%
43
 
3.2%
71
 
1.1%
181
 
1.1%
231
 
1.1%
311
 
1.1%
202011
 
11.7%
ValueCountFrequency (%)
202011
 
11.7%
311
 
1.1%
231
 
1.1%
181
 
1.1%
71
 
1.1%
43
 
3.2%
34
 
4.3%
218
 
19.1%
154
57.4%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct36
Distinct (%)38.7%
Missing1
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean26.88172043
Minimum1
Maximum349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:04.512818image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median10
Q323
95-th percentile77
Maximum349
Range348
Interquartile range (IQR)18

Descriptive statistics

Standard deviation58.17418549
Coefficient of variation (CV)2.1640797
Kurtosis21.52998351
Mean26.88172043
Median Absolute Deviation (MAD)6
Skewness4.551191901
Sum2500
Variance3384.235858
MonotonicityNot monotonic
2022-09-05T21:47:04.617795image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
17
 
7.4%
57
 
7.4%
26
 
6.4%
105
 
5.3%
45
 
5.3%
155
 
5.3%
35
 
5.3%
64
 
4.3%
94
 
4.3%
164
 
4.3%
Other values (26)41
43.6%
ValueCountFrequency (%)
17
7.4%
26
6.4%
35
5.3%
45
5.3%
57
7.4%
64
4.3%
74
4.3%
83
3.2%
94
4.3%
105
5.3%
ValueCountFrequency (%)
3491
1.1%
3141
1.1%
3131
1.1%
891
1.1%
861
1.1%
711
1.1%
661
1.1%
601
1.1%
542
2.1%
522
2.1%

type
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size880.0 B
regular
93 
significant_special
 
1

Length

Max length19
Median length7
Mean length7.127659574
Min length7

Characters and Unicode

Total characters670
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular93
98.9%
significant_special1
 
1.1%

Length

2022-09-05T21:47:04.709488image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:04.786621image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular93
98.9%
significant_special1
 
1.1%

Most occurring characters

ValueCountFrequency (%)
r186
27.8%
a95
14.2%
e94
14.0%
g94
14.0%
l94
14.0%
u93
13.9%
i4
 
0.6%
s2
 
0.3%
n2
 
0.3%
c2
 
0.3%
Other values (4)4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter669
99.9%
Connector Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r186
27.8%
a95
14.2%
e94
14.1%
g94
14.1%
l94
14.1%
u93
13.9%
i4
 
0.6%
s2
 
0.3%
n2
 
0.3%
c2
 
0.3%
Other values (3)3
 
0.4%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin669
99.9%
Common1
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
r186
27.8%
a95
14.2%
e94
14.1%
g94
14.1%
l94
14.1%
u93
13.9%
i4
 
0.6%
s2
 
0.3%
n2
 
0.3%
c2
 
0.3%
Other values (3)3
 
0.4%
Common
ValueCountFrequency (%)
_1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r186
27.8%
a95
14.2%
e94
14.0%
g94
14.0%
l94
14.0%
u93
13.9%
i4
 
0.6%
s2
 
0.3%
n2
 
0.3%
c2
 
0.3%
Other values (4)4
 
0.6%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size880.0 B
2020-12-22
94 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters940
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-22
2nd row2020-12-22
3rd row2020-12-22
4th row2020-12-22
5th row2020-12-22

Common Values

ValueCountFrequency (%)
2020-12-2294
100.0%

Length

2022-09-05T21:47:04.857506image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:04.928914image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-2294
100.0%

Most occurring characters

ValueCountFrequency (%)
2470
50.0%
0188
 
20.0%
-188
 
20.0%
194
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number752
80.0%
Dash Punctuation188
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2470
62.5%
0188
 
25.0%
194
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common940
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2470
50.0%
0188
 
20.0%
-188
 
20.0%
194
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2470
50.0%
0188
 
20.0%
-188
 
20.0%
194
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size880.0 B
69 
20:00
12 
10:00
 
2
17:00
 
2
22:00
 
2
Other values (7)

Length

Max length5
Median length0
Mean length1.329787234
Min length0

Characters and Unicode

Total characters125
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)7.4%

Sample

1st row12:00
2nd row
3rd row10:00
4th row10:00
5th row

Common Values

ValueCountFrequency (%)
69
73.4%
20:0012
 
12.8%
10:002
 
2.1%
17:002
 
2.1%
22:002
 
2.1%
12:001
 
1.1%
08:001
 
1.1%
06:001
 
1.1%
18:301
 
1.1%
20:451
 
1.1%
Other values (2)2
 
2.1%

Length

2022-09-05T21:47:05.001807image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0012
48.0%
10:002
 
8.0%
17:002
 
8.0%
22:002
 
8.0%
12:001
 
4.0%
08:001
 
4.0%
06:001
 
4.0%
18:301
 
4.0%
20:451
 
4.0%
08:301
 
4.0%

Most occurring characters

ValueCountFrequency (%)
064
51.2%
:25
 
20.0%
219
 
15.2%
16
 
4.8%
83
 
2.4%
72
 
1.6%
32
 
1.6%
52
 
1.6%
61
 
0.8%
41
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number100
80.0%
Other Punctuation25
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
064
64.0%
219
 
19.0%
16
 
6.0%
83
 
3.0%
72
 
2.0%
32
 
2.0%
52
 
2.0%
61
 
1.0%
41
 
1.0%
Other Punctuation
ValueCountFrequency (%)
:25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common125
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
064
51.2%
:25
 
20.0%
219
 
15.2%
16
 
4.8%
83
 
2.4%
72
 
1.6%
32
 
1.6%
52
 
1.6%
61
 
0.8%
41
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII125
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
064
51.2%
:25
 
20.0%
219
 
15.2%
16
 
4.8%
83
 
2.4%
72
 
1.6%
32
 
1.6%
52
 
1.6%
61
 
0.8%
41
 
0.8%

airstamp
Categorical

HIGH CORRELATION

Distinct19
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size880.0 B
2020-12-22T12:00:00+00:00
49 
2020-12-22T06:30:00+00:00
11 
2020-12-22T04:00:00+00:00
2020-12-22T17:00:00+00:00
 
4
2020-12-22T16:00:00+00:00
 
4
Other values (14)
20 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2350
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)9.6%

Sample

1st row2020-12-22T00:00:00+00:00
2nd row2020-12-22T00:00:00+00:00
3rd row2020-12-22T02:00:00+00:00
4th row2020-12-22T02:00:00+00:00
5th row2020-12-22T03:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-22T12:00:00+00:0049
52.1%
2020-12-22T06:30:00+00:0011
 
11.7%
2020-12-22T04:00:00+00:006
 
6.4%
2020-12-22T17:00:00+00:004
 
4.3%
2020-12-22T16:00:00+00:004
 
4.3%
2020-12-22T03:00:00+00:003
 
3.2%
2020-12-22T00:00:00+00:002
 
2.1%
2020-12-22T02:00:00+00:002
 
2.1%
2020-12-22T11:00:00+00:002
 
2.1%
2020-12-22T05:00:00+00:002
 
2.1%
Other values (9)9
 
9.6%

Length

2022-09-05T21:47:05.102917image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-22t12:00:00+00:0049
52.1%
2020-12-22t06:30:00+00:0011
 
11.7%
2020-12-22t04:00:00+00:006
 
6.4%
2020-12-22t17:00:00+00:004
 
4.3%
2020-12-22t16:00:00+00:004
 
4.3%
2020-12-22t03:00:00+00:003
 
3.2%
2020-12-22t11:00:00+00:002
 
2.1%
2020-12-22t05:00:00+00:002
 
2.1%
2020-12-22t02:00:00+00:002
 
2.1%
2020-12-22t00:00:00+00:002
 
2.1%
Other values (9)9
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0953
40.6%
2523
22.3%
:282
 
12.0%
-188
 
8.0%
1161
 
6.9%
T94
 
4.0%
+94
 
4.0%
319
 
0.8%
615
 
0.6%
48
 
0.3%
Other values (4)13
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1692
72.0%
Other Punctuation282
 
12.0%
Dash Punctuation188
 
8.0%
Uppercase Letter94
 
4.0%
Math Symbol94
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0953
56.3%
2523
30.9%
1161
 
9.5%
319
 
1.1%
615
 
0.9%
48
 
0.5%
56
 
0.4%
74
 
0.2%
92
 
0.1%
81
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:282
100.0%
Dash Punctuation
ValueCountFrequency (%)
-188
100.0%
Uppercase Letter
ValueCountFrequency (%)
T94
100.0%
Math Symbol
ValueCountFrequency (%)
+94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2256
96.0%
Latin94
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0953
42.2%
2523
23.2%
:282
 
12.5%
-188
 
8.3%
1161
 
7.1%
+94
 
4.2%
319
 
0.8%
615
 
0.7%
48
 
0.4%
56
 
0.3%
Other values (3)7
 
0.3%
Latin
ValueCountFrequency (%)
T94
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0953
40.6%
2523
22.3%
:282
 
12.0%
-188
 
8.0%
1161
 
6.9%
T94
 
4.0%
+94
 
4.0%
319
 
0.8%
615
 
0.6%
48
 
0.3%
Other values (4)13
 
0.6%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)35.2%
Missing3
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean30.0989011
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:05.195437image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q113
median20
Q343.5
95-th percentile90
Maximum120
Range119
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation25.33511176
Coefficient of variation (CV)0.8417287951
Kurtosis5.370156083
Mean30.0989011
Median Absolute Deviation (MAD)8
Skewness2.222542473
Sum2739
Variance641.8678877
MonotonicityNot monotonic
2022-09-05T21:47:05.299994image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
4514
14.9%
2014
14.9%
1310
 
10.6%
275
 
5.3%
1204
 
4.3%
154
 
4.3%
124
 
4.3%
304
 
4.3%
572
 
2.1%
182
 
2.1%
Other values (22)28
29.8%
(Missing)3
 
3.2%
ValueCountFrequency (%)
11
 
1.1%
41
 
1.1%
52
 
2.1%
72
 
2.1%
81
 
1.1%
102
 
2.1%
111
 
1.1%
124
 
4.3%
1310
10.6%
141
 
1.1%
ValueCountFrequency (%)
1204
 
4.3%
902
 
2.1%
572
 
2.1%
4514
14.9%
441
 
1.1%
431
 
1.1%
411
 
1.1%
391
 
1.1%
321
 
1.1%
304
 
4.3%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing94
Missing (%)100.0%
Memory size880.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct14
Distinct (%)100.0%
Missing80
Missing (%)85.1%
Memory size880.0 B
<p>This Christmas, Mike and the team return a milestone favor to Ashlee Smith, a young woman from Reno, Nevada who has been providing toys and hope to children affected by disasters since she was 8 years old.</p>
<p>Krist and Singto go on an excursion by air and sea as they ride a helicopter and a speedboat in this special episode. </p>
<p>DAY 4, Part One. Jennifer believes that her spell on Vee has backfired - she resorts to more serious ways to get what she wants. Meanwhile, Jay follows his own agenda, and Sister hears two confessions.</p>
<p>As a convalescing Mr. Roderick gives Father Severick orders to find the missing boy Sean, Ryan has left a voicemail for his brother Connor saying he's in trouble. Meanwhile, Ryan's girlfriend Susan follows her own path to find him but instead comes face to face with a very different Father Severick.</p>
<p>The loneliness of the season is taking a toll on both James and Dale. And they decide to do something about it. After all, nobody wants to be alone on Christmas.</p>
Other values (9)

Length

Max length804
Median length157
Mean length211.1428571
Min length60

Characters and Unicode

Total characters2956
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st row<p>This Christmas, Mike and the team return a milestone favor to Ashlee Smith, a young woman from Reno, Nevada who has been providing toys and hope to children affected by disasters since she was 8 years old.</p>
2nd row<p>Krist and Singto go on an excursion by air and sea as they ride a helicopter and a speedboat in this special episode. </p>
3rd row<p>DAY 4, Part One. Jennifer believes that her spell on Vee has backfired - she resorts to more serious ways to get what she wants. Meanwhile, Jay follows his own agenda, and Sister hears two confessions.</p>
4th row<p>As a convalescing Mr. Roderick gives Father Severick orders to find the missing boy Sean, Ryan has left a voicemail for his brother Connor saying he's in trouble. Meanwhile, Ryan's girlfriend Susan follows her own path to find him but instead comes face to face with a very different Father Severick.</p>
5th row<p>The loneliness of the season is taking a toll on both James and Dale. And they decide to do something about it. After all, nobody wants to be alone on Christmas.</p>

Common Values

ValueCountFrequency (%)
<p>This Christmas, Mike and the team return a milestone favor to Ashlee Smith, a young woman from Reno, Nevada who has been providing toys and hope to children affected by disasters since she was 8 years old.</p>1
 
1.1%
<p>Krist and Singto go on an excursion by air and sea as they ride a helicopter and a speedboat in this special episode. </p>1
 
1.1%
<p>DAY 4, Part One. Jennifer believes that her spell on Vee has backfired - she resorts to more serious ways to get what she wants. Meanwhile, Jay follows his own agenda, and Sister hears two confessions.</p>1
 
1.1%
<p>As a convalescing Mr. Roderick gives Father Severick orders to find the missing boy Sean, Ryan has left a voicemail for his brother Connor saying he's in trouble. Meanwhile, Ryan's girlfriend Susan follows her own path to find him but instead comes face to face with a very different Father Severick.</p>1
 
1.1%
<p>The loneliness of the season is taking a toll on both James and Dale. And they decide to do something about it. After all, nobody wants to be alone on Christmas.</p>1
 
1.1%
<p>Just as Kiki is getting ready to give Makoto her answer, Takumi suddenly appears and confesses he loves her. With Christmas fast approaching, the four friends—Kiki, Makoto, Takumi, and Riho—are still in a tangle of mixed-up emotions. Where will it all lead?</p>1
 
1.1%
<p>Diew's family moves to America, leaving him to make the transition to his college dorm all on his own where he meets some unique friends.  </p>1
 
1.1%
<p>'Ryo', who broke up with 'Chahan', 'Yuki Ehana,' 'Shiori Kato,' and 'Hitoko Murakami,' visits the ramen shop 'Satsumakko' for the first time in a while. So he hears from 'Murakami Tadashi' and 'Murakami Yoshie' that 'Chahhan' is out of order recently.<br />Ryo heads to the lesson studio for 'Chahhan'. Three people are surprised at the sudden visit of Ryo. Ryo enthusiastically scolds Yuki, Shiori, and Hitoko. Yuki is touched by Ryo's thoughts, and Shiori and Hitoko. Yuki goes to see the boy Ryo and she promises that she will definitely show success with 'pray'.<br />Three people who are making good progress toward their debut. Meanwhile, the color of the sky is changing more and more. The day when Ryo returns to the future is steadily approaching. 'Chahhan' invites Ryo to a one-man live.</p>1
 
1.1%
<p>Winnipeg Police find a victim who died in a stupid accident with no sign of violence.</p>1
 
1.1%
<p>Ryan uses Maisie to make illegal bets. She changes her plans and a few days later Ryan is found dead.</p>1
 
1.1%
Other values (4)4
 
4.3%
(Missing)80
85.1%

Length

2022-09-05T21:47:05.404331image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
to20
 
4.0%
and19
 
3.8%
the19
 
3.8%
a15
 
3.0%
of8
 
1.6%
is7
 
1.4%
she6
 
1.2%
ryo6
 
1.2%
in6
 
1.2%
her6
 
1.2%
Other values (301)385
77.5%

Most occurring characters

ValueCountFrequency (%)
482
16.3%
e259
 
8.8%
a192
 
6.5%
i181
 
6.1%
o174
 
5.9%
s172
 
5.8%
t163
 
5.5%
n143
 
4.8%
h136
 
4.6%
r127
 
4.3%
Other values (51)927
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2186
74.0%
Space Separator484
 
16.4%
Uppercase Letter111
 
3.8%
Other Punctuation108
 
3.7%
Math Symbol60
 
2.0%
Dash Punctuation5
 
0.2%
Decimal Number2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e259
11.8%
a192
 
8.8%
i181
 
8.3%
o174
 
8.0%
s172
 
7.9%
t163
 
7.5%
n143
 
6.5%
h136
 
6.2%
r127
 
5.8%
l87
 
4.0%
Other values (16)552
25.3%
Uppercase Letter
ValueCountFrequency (%)
S16
14.4%
R16
14.4%
M14
12.6%
C10
9.0%
T9
8.1%
A7
 
6.3%
Y6
 
5.4%
W5
 
4.5%
J4
 
3.6%
K4
 
3.6%
Other values (11)20
18.0%
Other Punctuation
ValueCountFrequency (%)
.33
30.6%
'29
26.9%
,27
25.0%
/16
14.8%
?2
 
1.9%
:1
 
0.9%
Space Separator
ValueCountFrequency (%)
482
99.6%
 2
 
0.4%
Math Symbol
ValueCountFrequency (%)
<30
50.0%
>30
50.0%
Dash Punctuation
ValueCountFrequency (%)
-3
60.0%
2
40.0%
Decimal Number
ValueCountFrequency (%)
41
50.0%
81
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2297
77.7%
Common659
 
22.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e259
 
11.3%
a192
 
8.4%
i181
 
7.9%
o174
 
7.6%
s172
 
7.5%
t163
 
7.1%
n143
 
6.2%
h136
 
5.9%
r127
 
5.5%
l87
 
3.8%
Other values (37)663
28.9%
Common
ValueCountFrequency (%)
482
73.1%
.33
 
5.0%
<30
 
4.6%
>30
 
4.6%
'29
 
4.4%
,27
 
4.1%
/16
 
2.4%
-3
 
0.5%
?2
 
0.3%
2
 
0.3%
Other values (4)5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII2949
99.8%
None5
 
0.2%
Punctuation2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
482
16.3%
e259
 
8.8%
a192
 
6.5%
i181
 
6.1%
o174
 
5.9%
s172
 
5.8%
t163
 
5.5%
n143
 
4.8%
h136
 
4.6%
r127
 
4.3%
Other values (48)920
31.2%
None
ValueCountFrequency (%)
é3
60.0%
 2
40.0%
Punctuation
ValueCountFrequency (%)
2
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)80.0%
Missing89
Missing (%)94.7%
Memory size880.0 B
7.5
9.5
8.5
7.7

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters15
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row9.5
2nd row7.5
3rd row8.5
4th row7.5
5th row7.7

Common Values

ValueCountFrequency (%)
7.52
 
2.1%
9.51
 
1.1%
8.51
 
1.1%
7.71
 
1.1%
(Missing)89
94.7%

Length

2022-09-05T21:47:05.491780image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:05.573801image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.52
40.0%
9.51
20.0%
8.51
20.0%
7.71
20.0%

Most occurring characters

ValueCountFrequency (%)
.5
33.3%
74
26.7%
54
26.7%
91
 
6.7%
81
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number10
66.7%
Other Punctuation5
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
74
40.0%
54
40.0%
91
 
10.0%
81
 
10.0%
Other Punctuation
ValueCountFrequency (%)
.5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.5
33.3%
74
26.7%
54
26.7%
91
 
6.7%
81
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.5
33.3%
74
26.7%
54
26.7%
91
 
6.7%
81
 
6.7%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size880.0 B
https://api.tvmaze.com/episodes/2007750
 
1
https://api.tvmaze.com/episodes/1988302
 
1
https://api.tvmaze.com/episodes/1992680
 
1
https://api.tvmaze.com/episodes/1992679
 
1
https://api.tvmaze.com/episodes/1992678
 
1
Other values (89)
89 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3666
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2007750
2nd rowhttps://api.tvmaze.com/episodes/2008030
3rd rowhttps://api.tvmaze.com/episodes/1964568
4th rowhttps://api.tvmaze.com/episodes/2052511
5th rowhttps://api.tvmaze.com/episodes/1993656

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/20077501
 
1.1%
https://api.tvmaze.com/episodes/19883021
 
1.1%
https://api.tvmaze.com/episodes/19926801
 
1.1%
https://api.tvmaze.com/episodes/19926791
 
1.1%
https://api.tvmaze.com/episodes/19926781
 
1.1%
https://api.tvmaze.com/episodes/19926771
 
1.1%
https://api.tvmaze.com/episodes/19926761
 
1.1%
https://api.tvmaze.com/episodes/19926751
 
1.1%
https://api.tvmaze.com/episodes/19926741
 
1.1%
https://api.tvmaze.com/episodes/19926731
 
1.1%
Other values (84)84
89.4%

Length

2022-09-05T21:47:05.646618image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/20077501
 
1.1%
https://api.tvmaze.com/episodes/20714941
 
1.1%
https://api.tvmaze.com/episodes/20525111
 
1.1%
https://api.tvmaze.com/episodes/19936561
 
1.1%
https://api.tvmaze.com/episodes/20962991
 
1.1%
https://api.tvmaze.com/episodes/23151171
 
1.1%
https://api.tvmaze.com/episodes/20683491
 
1.1%
https://api.tvmaze.com/episodes/20683511
 
1.1%
https://api.tvmaze.com/episodes/20057501
 
1.1%
https://api.tvmaze.com/episodes/20714931
 
1.1%
Other values (84)84
89.4%

Most occurring characters

ValueCountFrequency (%)
/376
 
10.3%
p282
 
7.7%
s282
 
7.7%
e282
 
7.7%
t282
 
7.7%
o188
 
5.1%
a188
 
5.1%
i188
 
5.1%
.188
 
5.1%
m188
 
5.1%
Other values (16)1222
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2350
64.1%
Other Punctuation658
 
17.9%
Decimal Number658
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p282
12.0%
s282
12.0%
e282
12.0%
t282
12.0%
o188
8.0%
a188
8.0%
i188
8.0%
m188
8.0%
h94
 
4.0%
d94
 
4.0%
Other values (3)282
12.0%
Decimal Number
ValueCountFrequency (%)
9136
20.7%
1120
18.2%
074
11.2%
765
9.9%
863
9.6%
260
9.1%
648
 
7.3%
434
 
5.2%
330
 
4.6%
528
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/376
57.1%
.188
28.6%
:94
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2350
64.1%
Common1316
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/376
28.6%
.188
14.3%
9136
 
10.3%
1120
 
9.1%
:94
 
7.1%
074
 
5.6%
765
 
4.9%
863
 
4.8%
260
 
4.6%
648
 
3.6%
Other values (3)92
 
7.0%
Latin
ValueCountFrequency (%)
p282
12.0%
s282
12.0%
e282
12.0%
t282
12.0%
o188
8.0%
a188
8.0%
i188
8.0%
m188
8.0%
h94
 
4.0%
d94
 
4.0%
Other values (3)282
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/376
 
10.3%
p282
 
7.7%
s282
 
7.7%
e282
 
7.7%
t282
 
7.7%
o188
 
5.1%
a188
 
5.1%
i188
 
5.1%
.188
 
5.1%
m188
 
5.1%
Other values (16)1222
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct60
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48381.20213
Minimum2504
Maximum63761
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:05.744709image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2504
5-th percentile15250
Q149276.75
median52526
Q352655
95-th percentile61061.35
Maximum63761
Range61257
Interquartile range (IQR)3378.25

Descriptive statistics

Standard deviation12188.72375
Coefficient of variation (CV)0.2519309817
Kurtosis4.566749355
Mean48381.20213
Median Absolute Deviation (MAD)588
Skewness-2.213547406
Sum4547833
Variance148564986.6
MonotonicityNot monotonic
2022-09-05T21:47:05.856270image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5252611
 
11.7%
5262910
 
10.6%
526554
 
4.3%
531144
 
4.3%
521073
 
3.2%
525242
 
2.1%
521042
 
2.1%
152502
 
2.1%
547622
 
2.1%
486732
 
2.1%
Other values (50)52
55.3%
ValueCountFrequency (%)
25041
1.1%
64411
1.1%
133811
1.1%
133921
1.1%
152502
2.1%
176331
1.1%
249631
1.1%
283471
1.1%
306061
1.1%
329801
1.1%
ValueCountFrequency (%)
637611
1.1%
637191
1.1%
617551
1.1%
616741
1.1%
615301
1.1%
608091
1.1%
607851
1.1%
583671
1.1%
573391
1.1%
550161
1.1%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct60
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Memory size880.0 B
https://www.tvmaze.com/shows/52526/whos-your-daddy
11 
https://www.tvmaze.com/shows/52629/rhyme-time-town-singalongs
10 
https://www.tvmaze.com/shows/52655/the-case-solver
 
4
https://www.tvmaze.com/shows/53114/edgar
 
4
https://www.tvmaze.com/shows/52107/new-face
 
3
Other values (55)
62 

Length

Max length68
Median length61
Mean length51.75531915
Min length40

Characters and Unicode

Total characters4865
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)51.1%

Sample

1st rowhttps://www.tvmaze.com/shows/51065/stand-up-autsajd
2nd rowhttps://www.tvmaze.com/shows/52933/lab-s-antonom-belaevym
3rd rowhttps://www.tvmaze.com/shows/51336/core-sense
4th rowhttps://www.tvmaze.com/shows/54033/wu-shen-zhu-zai
5th rowhttps://www.tvmaze.com/shows/44276/7-days-of-romance

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52526/whos-your-daddy11
 
11.7%
https://www.tvmaze.com/shows/52629/rhyme-time-town-singalongs10
 
10.6%
https://www.tvmaze.com/shows/52655/the-case-solver4
 
4.3%
https://www.tvmaze.com/shows/53114/edgar4
 
4.3%
https://www.tvmaze.com/shows/52107/new-face3
 
3.2%
https://www.tvmaze.com/shows/52524/forever-love2
 
2.1%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.1%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.1%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
2.1%
https://www.tvmaze.com/shows/48673/doomsday-awakening2
 
2.1%
Other values (50)52
55.3%

Length

2022-09-05T21:47:05.960356image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52526/whos-your-daddy11
 
11.7%
https://www.tvmaze.com/shows/52629/rhyme-time-town-singalongs10
 
10.6%
https://www.tvmaze.com/shows/52655/the-case-solver4
 
4.3%
https://www.tvmaze.com/shows/53114/edgar4
 
4.3%
https://www.tvmaze.com/shows/52107/new-face3
 
3.2%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
2.1%
https://www.tvmaze.com/shows/52400/dream-detective2
 
2.1%
https://www.tvmaze.com/shows/48673/doomsday-awakening2
 
2.1%
https://www.tvmaze.com/shows/52159/to-love2
 
2.1%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.1%
Other values (50)52
55.3%

Most occurring characters

ValueCountFrequency (%)
/470
 
9.7%
w415
 
8.5%
t382
 
7.9%
s375
 
7.7%
o309
 
6.4%
e257
 
5.3%
h243
 
5.0%
m236
 
4.9%
a206
 
4.2%
.188
 
3.9%
Other values (30)1784
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3460
71.1%
Other Punctuation752
 
15.5%
Decimal Number471
 
9.7%
Dash Punctuation182
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w415
12.0%
t382
11.0%
s375
10.8%
o309
 
8.9%
e257
 
7.4%
h243
 
7.0%
m236
 
6.8%
a206
 
6.0%
v122
 
3.5%
c120
 
3.5%
Other values (16)795
23.0%
Decimal Number
ValueCountFrequency (%)
5104
22.1%
293
19.7%
652
11.0%
442
8.9%
140
 
8.5%
338
 
8.1%
033
 
7.0%
728
 
5.9%
924
 
5.1%
817
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/470
62.5%
.188
 
25.0%
:94
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3460
71.1%
Common1405
28.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
w415
12.0%
t382
11.0%
s375
10.8%
o309
 
8.9%
e257
 
7.4%
h243
 
7.0%
m236
 
6.8%
a206
 
6.0%
v122
 
3.5%
c120
 
3.5%
Other values (16)795
23.0%
Common
ValueCountFrequency (%)
/470
33.5%
.188
 
13.4%
-182
 
13.0%
5104
 
7.4%
:94
 
6.7%
293
 
6.6%
652
 
3.7%
442
 
3.0%
140
 
2.8%
338
 
2.7%
Other values (4)102
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII4865
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/470
 
9.7%
w415
 
8.5%
t382
 
7.9%
s375
 
7.7%
o309
 
6.4%
e257
 
5.3%
h243
 
5.0%
m236
 
4.9%
a206
 
4.2%
.188
 
3.9%
Other values (30)1784
36.7%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct60
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Memory size880.0 B
Who's Your Daddy?
11 
Rhyme Time Town Singalongs
10 
The Case Solver
 
4
Edgar
 
4
New Face
 
3
Other values (55)
62 

Length

Max length33
Median length26
Mean length17.07446809
Min length5

Characters and Unicode

Total characters1605
Distinct characters81
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)51.1%

Sample

1st rowStand Up Аутсайд
2nd rowLAB с Антоном Беляевым
3rd rowCore Sense
4th rowWu Shen Zhu Zai
5th row7 Days of Romance

Common Values

ValueCountFrequency (%)
Who's Your Daddy?11
 
11.7%
Rhyme Time Town Singalongs10
 
10.6%
The Case Solver4
 
4.3%
Edgar4
 
4.3%
New Face3
 
3.2%
Forever Love2
 
2.1%
Twisted Fate of Love2
 
2.1%
The Young Turks2
 
2.1%
Youths in the Breeze2
 
2.1%
Doomsday Awakening2
 
2.1%
Other values (50)52
55.3%

Length

2022-09-05T21:47:06.067409image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the12
 
4.4%
who's11
 
4.0%
your11
 
4.0%
daddy11
 
4.0%
rhyme10
 
3.6%
time10
 
3.6%
town10
 
3.6%
singalongs10
 
3.6%
love7
 
2.5%
of5
 
1.8%
Other values (142)178
64.7%

Most occurring characters

ValueCountFrequency (%)
181
 
11.3%
e150
 
9.3%
o117
 
7.3%
a91
 
5.7%
n87
 
5.4%
i78
 
4.9%
r67
 
4.2%
s65
 
4.0%
t54
 
3.4%
h51
 
3.2%
Other values (71)664
41.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1131
70.5%
Uppercase Letter262
 
16.3%
Space Separator181
 
11.3%
Other Punctuation27
 
1.7%
Decimal Number3
 
0.2%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e150
13.3%
o117
 
10.3%
a91
 
8.0%
n87
 
7.7%
i78
 
6.9%
r67
 
5.9%
s65
 
5.7%
t54
 
4.8%
h51
 
4.5%
d50
 
4.4%
Other values (33)321
28.4%
Uppercase Letter
ValueCountFrequency (%)
T42
16.0%
S25
 
9.5%
D24
 
9.2%
R17
 
6.5%
A17
 
6.5%
Y17
 
6.5%
W16
 
6.1%
L13
 
5.0%
F12
 
4.6%
C11
 
4.2%
Other values (18)68
26.0%
Other Punctuation
ValueCountFrequency (%)
'12
44.4%
?11
40.7%
.2
 
7.4%
:1
 
3.7%
,1
 
3.7%
Decimal Number
ValueCountFrequency (%)
71
33.3%
01
33.3%
21
33.3%
Space Separator
ValueCountFrequency (%)
181
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1356
84.5%
Common212
 
13.2%
Cyrillic37
 
2.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e150
 
11.1%
o117
 
8.6%
a91
 
6.7%
n87
 
6.4%
i78
 
5.8%
r67
 
4.9%
s65
 
4.8%
t54
 
4.0%
h51
 
3.8%
d50
 
3.7%
Other values (40)546
40.3%
Cyrillic
ValueCountFrequency (%)
е5
13.5%
т4
 
10.8%
н3
 
8.1%
с3
 
8.1%
в3
 
8.1%
о2
 
5.4%
м2
 
5.4%
А2
 
5.4%
л1
 
2.7%
Б1
 
2.7%
Other values (11)11
29.7%
Common
ValueCountFrequency (%)
181
85.4%
'12
 
5.7%
?11
 
5.2%
.2
 
0.9%
-1
 
0.5%
:1
 
0.5%
71
 
0.5%
01
 
0.5%
21
 
0.5%
,1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1567
97.6%
Cyrillic37
 
2.3%
None1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
181
 
11.6%
e150
 
9.6%
o117
 
7.5%
a91
 
5.8%
n87
 
5.6%
i78
 
5.0%
r67
 
4.3%
s65
 
4.1%
t54
 
3.4%
h51
 
3.3%
Other values (49)626
39.9%
Cyrillic
ValueCountFrequency (%)
е5
13.5%
т4
 
10.8%
н3
 
8.1%
с3
 
8.1%
в3
 
8.1%
о2
 
5.4%
м2
 
5.4%
А2
 
5.4%
л1
 
2.7%
Б1
 
2.7%
Other values (11)11
29.7%
None
ValueCountFrequency (%)
ø1
100.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size880.0 B
Scripted
51 
Animation
17 
Talk Show
Documentary
 
5
Reality
 
5
Other values (3)
10 

Length

Max length11
Median length8
Mean length8.095744681
Min length4

Characters and Unicode

Total characters761
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVariety
2nd rowDocumentary
3rd rowAnimation
4th rowAnimation
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted51
54.3%
Animation17
 
18.1%
Talk Show6
 
6.4%
Documentary5
 
5.3%
Reality5
 
5.3%
Sports5
 
5.3%
News3
 
3.2%
Variety2
 
2.1%

Length

2022-09-05T21:47:06.165018image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:06.259413image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted51
51.0%
animation17
 
17.0%
talk6
 
6.0%
show6
 
6.0%
documentary5
 
5.0%
reality5
 
5.0%
sports5
 
5.0%
news3
 
3.0%
variety2
 
2.0%

Most occurring characters

ValueCountFrequency (%)
i92
12.1%
t85
11.2%
e66
8.7%
r63
8.3%
S62
 
8.1%
p56
 
7.4%
c56
 
7.4%
d51
 
6.7%
n39
 
5.1%
a35
 
4.6%
Other values (16)156
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter655
86.1%
Uppercase Letter100
 
13.1%
Space Separator6
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i92
14.0%
t85
13.0%
e66
10.1%
r63
9.6%
p56
8.5%
c56
8.5%
d51
7.8%
n39
6.0%
a35
 
5.3%
o33
 
5.0%
Other values (8)79
12.1%
Uppercase Letter
ValueCountFrequency (%)
S62
62.0%
A17
 
17.0%
T6
 
6.0%
D5
 
5.0%
R5
 
5.0%
N3
 
3.0%
V2
 
2.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin755
99.2%
Common6
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
i92
12.2%
t85
11.3%
e66
8.7%
r63
8.3%
S62
8.2%
p56
 
7.4%
c56
 
7.4%
d51
 
6.8%
n39
 
5.2%
a35
 
4.6%
Other values (15)150
19.9%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII761
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i92
12.1%
t85
11.2%
e66
8.7%
r63
8.3%
S62
 
8.1%
p56
 
7.4%
c56
 
7.4%
d51
 
6.7%
n39
 
5.1%
a35
 
4.6%
Other values (16)156
20.5%

_embedded.show.language
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)15.1%
Missing1
Missing (%)1.1%
Memory size880.0 B
English
30 
Chinese
24 
Hindi
11 
Japanese
Korean
Other values (9)
19 

Length

Max length9
Median length7
Mean length6.720430108
Min length4

Characters and Unicode

Total characters625
Distinct characters30
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)4.3%

Sample

1st rowRussian
2nd rowRussian
3rd rowChinese
4th rowChinese
5th rowKorean

Common Values

ValueCountFrequency (%)
English30
31.9%
Chinese24
25.5%
Hindi11
 
11.7%
Japanese5
 
5.3%
Korean4
 
4.3%
Norwegian4
 
4.3%
French4
 
4.3%
Russian3
 
3.2%
Thai2
 
2.1%
Tagalog2
 
2.1%
Other values (4)4
 
4.3%

Length

2022-09-05T21:47:06.348075image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english30
32.3%
chinese24
25.8%
hindi11
 
11.8%
japanese5
 
5.4%
korean4
 
4.3%
norwegian4
 
4.3%
french4
 
4.3%
russian3
 
3.2%
thai2
 
2.2%
tagalog2
 
2.2%
Other values (4)4
 
4.3%

Most occurring characters

ValueCountFrequency (%)
i88
14.1%
n87
13.9%
e71
11.4%
s67
10.7%
h62
9.9%
g38
 
6.1%
l32
 
5.1%
E30
 
4.8%
a30
 
4.8%
C24
 
3.8%
Other values (20)96
15.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter532
85.1%
Uppercase Letter93
 
14.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i88
16.5%
n87
16.4%
e71
13.3%
s67
12.6%
h62
11.7%
g38
7.1%
l32
 
6.0%
a30
 
5.6%
r14
 
2.6%
d11
 
2.1%
Other values (7)32
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
E30
32.3%
C24
25.8%
H11
 
11.8%
J5
 
5.4%
K4
 
4.3%
N4
 
4.3%
F4
 
4.3%
T4
 
4.3%
R3
 
3.2%
P1
 
1.1%
Other values (3)3
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Latin625
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i88
14.1%
n87
13.9%
e71
11.4%
s67
10.7%
h62
9.9%
g38
 
6.1%
l32
 
5.1%
E30
 
4.8%
a30
 
4.8%
C24
 
3.8%
Other values (20)96
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i88
14.1%
n87
13.9%
e71
11.4%
s67
10.7%
h62
9.9%
g38
 
6.1%
l32
 
5.1%
E30
 
4.8%
a30
 
4.8%
C24
 
3.8%
Other values (20)96
15.4%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size880.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size880.0 B
Running
48 
Ended
31 
To Be Determined
15 

Length

Max length16
Median length7
Mean length7.776595745
Min length5

Characters and Unicode

Total characters731
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowTo Be Determined
3rd rowRunning
4th rowRunning
5th rowEnded

Common Values

ValueCountFrequency (%)
Running48
51.1%
Ended31
33.0%
To Be Determined15
 
16.0%

Length

2022-09-05T21:47:06.436458image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:06.518728image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running48
38.7%
ended31
25.0%
to15
 
12.1%
be15
 
12.1%
determined15
 
12.1%

Most occurring characters

ValueCountFrequency (%)
n190
26.0%
e91
12.4%
d77
10.5%
i63
 
8.6%
R48
 
6.6%
u48
 
6.6%
g48
 
6.6%
E31
 
4.2%
30
 
4.1%
T15
 
2.1%
Other values (6)90
12.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter577
78.9%
Uppercase Letter124
 
17.0%
Space Separator30
 
4.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n190
32.9%
e91
15.8%
d77
13.3%
i63
 
10.9%
u48
 
8.3%
g48
 
8.3%
o15
 
2.6%
t15
 
2.6%
r15
 
2.6%
m15
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
R48
38.7%
E31
25.0%
T15
 
12.1%
B15
 
12.1%
D15
 
12.1%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin701
95.9%
Common30
 
4.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n190
27.1%
e91
13.0%
d77
11.0%
i63
 
9.0%
R48
 
6.8%
u48
 
6.8%
g48
 
6.8%
E31
 
4.4%
T15
 
2.1%
o15
 
2.1%
Other values (5)75
 
10.7%
Common
ValueCountFrequency (%)
30
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII731
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n190
26.0%
e91
12.4%
d77
10.5%
i63
 
8.6%
R48
 
6.6%
u48
 
6.6%
g48
 
6.6%
E31
 
4.2%
30
 
4.1%
T15
 
2.1%
Other values (6)90
12.3%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct23
Distinct (%)29.9%
Missing17
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean30.80519481
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:06.590476image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q113
median20
Q345
95-th percentile96
Maximum120
Range119
Interquartile range (IQR)32

Descriptive statistics

Standard deviation26.0541132
Coefficient of variation (CV)0.8457701166
Kurtosis5.278761625
Mean30.80519481
Median Absolute Deviation (MAD)10
Skewness2.207771834
Sum2372
Variance678.8168148
MonotonicityNot monotonic
2022-09-05T21:47:06.690347image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
4514
14.9%
2014
14.9%
1310
10.6%
305
 
5.3%
154
 
4.3%
344
 
4.3%
1204
 
4.3%
253
 
3.2%
572
 
2.1%
72
 
2.1%
Other values (13)15
16.0%
(Missing)17
18.1%
ValueCountFrequency (%)
11
 
1.1%
41
 
1.1%
51
 
1.1%
72
 
2.1%
81
 
1.1%
102
 
2.1%
111
 
1.1%
122
 
2.1%
1310
10.6%
154
 
4.3%
ValueCountFrequency (%)
1204
 
4.3%
901
 
1.1%
572
 
2.1%
4514
14.9%
401
 
1.1%
344
 
4.3%
305
 
5.3%
271
 
1.1%
261
 
1.1%
253
 
3.2%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)34.8%
Missing2
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean29.40217391
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:06.783193image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q113
median20.5
Q342
95-th percentile90
Maximum120
Range119
Interquartile range (IQR)29

Descriptive statistics

Standard deviation24.6135225
Coefficient of variation (CV)0.837132743
Kurtosis5.154783122
Mean29.40217391
Median Absolute Deviation (MAD)8.5
Skewness2.158784514
Sum2705
Variance605.8254897
MonotonicityNot monotonic
2022-09-05T21:47:06.893887image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
4513
13.8%
1911
 
11.7%
1310
 
10.6%
307
 
7.4%
125
 
5.3%
424
 
4.3%
154
 
4.3%
1203
 
3.2%
253
 
3.2%
263
 
3.2%
Other values (22)29
30.9%
ValueCountFrequency (%)
11
 
1.1%
41
 
1.1%
51
 
1.1%
61
 
1.1%
72
 
2.1%
81
 
1.1%
91
 
1.1%
102
 
2.1%
112
 
2.1%
125
5.3%
ValueCountFrequency (%)
1203
 
3.2%
981
 
1.1%
902
 
2.1%
591
 
1.1%
571
 
1.1%
4513
13.8%
424
 
4.3%
381
 
1.1%
307
7.4%
282
 
2.1%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct47
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size880.0 B
2020-12-22
12 
2020-04-02
11 
2020-12-21
2020-11-24
 
4
2020-08-05
 
4
Other values (42)
57 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters940
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)31.9%

Sample

1st row2020-10-13
2nd row2019-12-17
3rd row2020-10-13
4th row2020-03-08
5th row2019-10-08

Common Values

ValueCountFrequency (%)
2020-12-2212
 
12.8%
2020-04-0211
 
11.7%
2020-12-216
 
6.4%
2020-11-244
 
4.3%
2020-08-054
 
4.3%
2020-12-013
 
3.2%
2020-12-083
 
3.2%
2020-10-203
 
3.2%
2020-11-192
 
2.1%
2020-12-142
 
2.1%
Other values (37)44
46.8%

Length

2022-09-05T21:47:06.983420image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-2212
 
12.8%
2020-04-0211
 
11.7%
2020-12-216
 
6.4%
2020-11-244
 
4.3%
2020-08-054
 
4.3%
2020-12-013
 
3.2%
2020-12-083
 
3.2%
2020-10-203
 
3.2%
2020-10-132
 
2.1%
2020-11-232
 
2.1%
Other values (37)44
46.8%

Most occurring characters

ValueCountFrequency (%)
2260
27.7%
0249
26.5%
-188
20.0%
1129
13.7%
427
 
2.9%
924
 
2.6%
823
 
2.4%
316
 
1.7%
514
 
1.5%
78
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number752
80.0%
Dash Punctuation188
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2260
34.6%
0249
33.1%
1129
17.2%
427
 
3.6%
924
 
3.2%
823
 
3.1%
316
 
2.1%
514
 
1.9%
78
 
1.1%
62
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common940
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2260
27.7%
0249
26.5%
-188
20.0%
1129
13.7%
427
 
2.9%
924
 
2.6%
823
 
2.4%
316
 
1.7%
514
 
1.5%
78
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2260
27.7%
0249
26.5%
-188
20.0%
1129
13.7%
427
 
2.9%
924
 
2.6%
823
 
2.4%
316
 
1.7%
514
 
1.5%
78
 
0.9%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)45.2%
Missing63
Missing (%)67.0%
Memory size880.0 B
2020-12-22
2021-01-05
2022-05-02
2020-12-31
2020-12-30
Other values (9)
10 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters310
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)25.8%

Sample

1st row2020-12-31
2nd row2021-01-20
3rd row2021-01-06
4th row2020-12-22
5th row2020-12-31

Common Values

ValueCountFrequency (%)
2020-12-228
 
8.5%
2021-01-055
 
5.3%
2022-05-024
 
4.3%
2020-12-312
 
2.1%
2020-12-302
 
2.1%
2020-12-232
 
2.1%
2021-01-201
 
1.1%
2021-01-061
 
1.1%
2020-12-241
 
1.1%
2021-02-161
 
1.1%
Other values (4)4
 
4.3%
(Missing)63
67.0%

Length

2022-09-05T21:47:07.064721image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-228
25.8%
2021-01-055
16.1%
2022-05-024
12.9%
2020-12-312
 
6.5%
2020-12-302
 
6.5%
2020-12-232
 
6.5%
2021-01-201
 
3.2%
2021-01-061
 
3.2%
2020-12-241
 
3.2%
2021-02-161
 
3.2%
Other values (4)4
12.9%

Most occurring characters

ValueCountFrequency (%)
2111
35.8%
077
24.8%
-62
20.0%
137
 
11.9%
510
 
3.2%
37
 
2.3%
63
 
1.0%
92
 
0.6%
41
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number248
80.0%
Dash Punctuation62
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2111
44.8%
077
31.0%
137
 
14.9%
510
 
4.0%
37
 
2.8%
63
 
1.2%
92
 
0.8%
41
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
-62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2111
35.8%
077
24.8%
-62
20.0%
137
 
11.9%
510
 
3.2%
37
 
2.3%
63
 
1.0%
92
 
0.6%
41
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2111
35.8%
077
24.8%
-62
20.0%
137
 
11.9%
510
 
3.2%
37
 
2.3%
63
 
1.0%
92
 
0.6%
41
 
0.3%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct51
Distinct (%)60.0%
Missing9
Missing (%)9.6%
Memory size880.0 B
https://www.altbalaji.com/show/whos-your-daddy/333
11 
https://www.netflix.com/title/81221345
10 
https://www.crave.ca/en/tv-shows/edgar
 
4
https://www.iqiyi.com/a_c4m3iuc94t.html
 
4
https://v.qq.com/detail/m/mzc00200tu76tos.html
 
3
Other values (46)
53 

Length

Max length105
Median length74
Mean length48.05882353
Min length18

Characters and Unicode

Total characters4085
Distinct characters73
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)45.9%

Sample

1st rowhttps://premier.one/show/13734
2nd rowhttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva
3rd rowhttps://www.bilibili.com/bangumi/media/md28223064
4th rowhttps://v.qq.com/detail/m/7q544xyrava3vxf.html
5th rowhttps://www.paravi.jp/static/koisuko

Common Values

ValueCountFrequency (%)
https://www.altbalaji.com/show/whos-your-daddy/33311
 
11.7%
https://www.netflix.com/title/8122134510
 
10.6%
https://www.crave.ca/en/tv-shows/edgar4
 
4.3%
https://www.iqiyi.com/a_c4m3iuc94t.html4
 
4.3%
https://v.qq.com/detail/m/mzc00200tu76tos.html3
 
3.2%
https://v.qq.com/detail/j/jaqpncskrgv28oo.html2
 
2.1%
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
2.1%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
2.1%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.1%
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=12
 
2.1%
Other values (41)43
45.7%
(Missing)9
 
9.6%

Length

2022-09-05T21:47:07.170648image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.altbalaji.com/show/whos-your-daddy/33311
 
12.9%
https://www.netflix.com/title/8122134510
 
11.8%
https://www.crave.ca/en/tv-shows/edgar4
 
4.7%
https://www.iqiyi.com/a_c4m3iuc94t.html4
 
4.7%
https://v.qq.com/detail/m/mzc00200tu76tos.html3
 
3.5%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.4%
https://www.tytnetwork.com2
 
2.4%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
2.4%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.4%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
2.4%
Other values (41)43
50.6%

Most occurring characters

ValueCountFrequency (%)
/357
 
8.7%
t337
 
8.2%
w209
 
5.1%
o191
 
4.7%
s190
 
4.7%
.189
 
4.6%
h162
 
4.0%
a152
 
3.7%
e149
 
3.6%
m128
 
3.1%
Other values (63)2021
49.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2669
65.3%
Other Punctuation709
 
17.4%
Decimal Number428
 
10.5%
Uppercase Letter181
 
4.4%
Dash Punctuation55
 
1.3%
Math Symbol25
 
0.6%
Connector Punctuation18
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t337
 
12.6%
w209
 
7.8%
o191
 
7.2%
s190
 
7.1%
h162
 
6.1%
a152
 
5.7%
e149
 
5.6%
m128
 
4.8%
c123
 
4.6%
i123
 
4.6%
Other values (16)905
33.9%
Uppercase Letter
ValueCountFrequency (%)
E24
 
13.3%
A13
 
7.2%
B13
 
7.2%
C10
 
5.5%
T10
 
5.5%
D9
 
5.0%
F9
 
5.0%
J9
 
5.0%
P9
 
5.0%
W8
 
4.4%
Other values (15)67
37.0%
Decimal Number
ValueCountFrequency (%)
370
16.4%
158
13.6%
253
12.4%
453
12.4%
046
10.7%
843
10.0%
536
8.4%
928
 
6.5%
721
 
4.9%
620
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/357
50.4%
.189
26.7%
:85
 
12.0%
%57
 
8.0%
?12
 
1.7%
&7
 
1.0%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=23
92.0%
+2
 
8.0%
Dash Punctuation
ValueCountFrequency (%)
-55
100.0%
Connector Punctuation
ValueCountFrequency (%)
_18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2850
69.8%
Common1235
30.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t337
 
11.8%
w209
 
7.3%
o191
 
6.7%
s190
 
6.7%
h162
 
5.7%
a152
 
5.3%
e149
 
5.2%
m128
 
4.5%
c123
 
4.3%
i123
 
4.3%
Other values (41)1086
38.1%
Common
ValueCountFrequency (%)
/357
28.9%
.189
15.3%
:85
 
6.9%
370
 
5.7%
158
 
4.7%
%57
 
4.6%
-55
 
4.5%
253
 
4.3%
453
 
4.3%
046
 
3.7%
Other values (12)212
17.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII4085
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/357
 
8.7%
t337
 
8.2%
w209
 
5.1%
o191
 
4.7%
s190
 
4.7%
.189
 
4.6%
h162
 
4.0%
a152
 
3.7%
e149
 
3.6%
m128
 
3.1%
Other values (63)2021
49.5%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size880.0 B
68 
20:00
12 
22:00
 
3
10:00
 
2
17:00
 
2
Other values (7)

Length

Max length5
Median length0
Mean length1.382978723
Min length0

Characters and Unicode

Total characters130
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)7.4%

Sample

1st row
2nd row23:45
3rd row10:00
4th row10:00
5th row

Common Values

ValueCountFrequency (%)
68
72.3%
20:0012
 
12.8%
22:003
 
3.2%
10:002
 
2.1%
17:002
 
2.1%
23:451
 
1.1%
19:001
 
1.1%
08:001
 
1.1%
06:001
 
1.1%
20:451
 
1.1%
Other values (2)2
 
2.1%

Length

2022-09-05T21:47:07.285211image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0012
46.2%
22:003
 
11.5%
10:002
 
7.7%
17:002
 
7.7%
23:451
 
3.8%
19:001
 
3.8%
08:001
 
3.8%
06:001
 
3.8%
20:451
 
3.8%
08:301
 
3.8%

Most occurring characters

ValueCountFrequency (%)
065
50.0%
:26
 
20.0%
221
 
16.2%
15
 
3.8%
53
 
2.3%
72
 
1.5%
32
 
1.5%
42
 
1.5%
82
 
1.5%
91
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number104
80.0%
Other Punctuation26
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
065
62.5%
221
 
20.2%
15
 
4.8%
53
 
2.9%
72
 
1.9%
32
 
1.9%
42
 
1.9%
82
 
1.9%
91
 
1.0%
61
 
1.0%
Other Punctuation
ValueCountFrequency (%)
:26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
065
50.0%
:26
 
20.0%
221
 
16.2%
15
 
3.8%
53
 
2.3%
72
 
1.5%
32
 
1.5%
42
 
1.5%
82
 
1.5%
91
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
065
50.0%
:26
 
20.0%
221
 
16.2%
15
 
3.8%
53
 
2.3%
72
 
1.5%
32
 
1.5%
42
 
1.5%
82
 
1.5%
91
 
0.8%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size880.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing92
Missing (%)97.9%
Memory size880.0 B
7.8
5.8

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row7.8
2nd row5.8

Common Values

ValueCountFrequency (%)
7.81
 
1.1%
5.81
 
1.1%
(Missing)92
97.9%

Length

2022-09-05T21:47:07.383579image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:07.471033image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.81
50.0%
5.81
50.0%

Most occurring characters

ValueCountFrequency (%)
.2
33.3%
82
33.3%
71
16.7%
51
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number4
66.7%
Other Punctuation2
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
82
50.0%
71
25.0%
51
25.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.2
33.3%
82
33.3%
71
16.7%
51
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.2
33.3%
82
33.3%
71
16.7%
51
16.7%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct40
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.55319149
Minimum1
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:07.555231image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.65
Q115
median25
Q333.75
95-th percentile80
Maximum94
Range93
Interquartile range (IQR)18.75

Descriptive statistics

Standard deviation21.3806349
Coefficient of variation (CV)0.7234628081
Kurtosis1.218246088
Mean29.55319149
Median Absolute Deviation (MAD)9
Skewness1.330686953
Sum2778
Variance457.1315488
MonotonicityNot monotonic
2022-09-05T21:47:07.664699image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1512
 
12.8%
2511
 
11.7%
216
 
6.4%
346
 
6.4%
276
 
6.4%
194
 
4.3%
303
 
3.2%
13
 
3.2%
802
 
2.1%
242
 
2.1%
Other values (30)39
41.5%
ValueCountFrequency (%)
13
 
3.2%
32
 
2.1%
42
 
2.1%
51
 
1.1%
72
 
2.1%
81
 
1.1%
91
 
1.1%
101
 
1.1%
131
 
1.1%
1512
12.8%
ValueCountFrequency (%)
941
1.1%
831
1.1%
821
1.1%
811
1.1%
802
2.1%
761
1.1%
752
2.1%
711
1.1%
621
1.1%
601
1.1%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing94
Missing (%)100.0%
Memory size880.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)37.0%
Missing2
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean151.9456522
Minimum1
Maximum516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:07.757701image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q121
median104
Q3313
95-th percentile380.45
Maximum516
Range515
Interquartile range (IQR)292

Descriptive statistics

Standard deviation143.0795801
Coefficient of variation (CV)0.9416497153
Kurtosis-0.700337666
Mean151.9456522
Median Absolute Deviation (MAD)83
Skewness0.7562911859
Sum13979
Variance20471.76624
MonotonicityNot monotonic
2022-09-05T21:47:07.866108image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2116
17.0%
10413
13.8%
33511
11.7%
110
10.6%
1094
 
4.3%
674
 
4.3%
1184
 
4.3%
3272
 
2.1%
2022
 
2.1%
302
 
2.1%
Other values (24)24
25.5%
(Missing)2
 
2.1%
ValueCountFrequency (%)
110
10.6%
21
 
1.1%
31
 
1.1%
2116
17.0%
302
 
2.1%
511
 
1.1%
674
 
4.3%
881
 
1.1%
1021
 
1.1%
10413
13.8%
ValueCountFrequency (%)
5161
 
1.1%
5071
 
1.1%
4451
 
1.1%
4141
 
1.1%
3811
 
1.1%
3801
 
1.1%
3791
 
1.1%
3721
 
1.1%
3421
 
1.1%
33511
11.7%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct34
Distinct (%)37.0%
Missing2
Missing (%)2.1%
Memory size880.0 B
YouTube
16 
Tencent QQ
13 
ALT Balaji
11 
Netflix
10 
CraveTV
Other values (29)
38 

Length

Max length17
Median length14
Mean length8.119565217
Min length3

Characters and Unicode

Total characters747
Distinct characters57
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)26.1%

Sample

1st rowYouTube
2nd rowКиноПоиск HD
3rd rowBilibili
4th rowTencent QQ
5th rowSeezn

Common Values

ValueCountFrequency (%)
YouTube16
17.0%
Tencent QQ13
13.8%
ALT Balaji11
11.7%
Netflix10
10.6%
CraveTV4
 
4.3%
iQIYI4
 
4.3%
Youku4
 
4.3%
TV 2 Play2
 
2.1%
Facebook Watch2
 
2.1%
Naver TVCast2
 
2.1%
Other values (24)24
25.5%
(Missing)2
 
2.1%

Length

2022-09-05T21:47:07.965863image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube16
 
11.8%
qq13
 
9.6%
tencent13
 
9.6%
alt11
 
8.1%
balaji11
 
8.1%
netflix10
 
7.4%
tv6
 
4.4%
cravetv4
 
2.9%
iqiyi4
 
2.9%
youku4
 
2.9%
Other values (36)44
32.4%

Most occurring characters

ValueCountFrequency (%)
e72
 
9.6%
T56
 
7.5%
u45
 
6.0%
a45
 
6.0%
44
 
5.9%
i40
 
5.4%
t34
 
4.6%
o34
 
4.6%
l31
 
4.1%
Q30
 
4.0%
Other values (47)316
42.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter468
62.7%
Uppercase Letter231
30.9%
Space Separator44
 
5.9%
Decimal Number2
 
0.3%
Math Symbol1
 
0.1%
Other Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e72
15.4%
u45
9.6%
a45
9.6%
i40
8.5%
t34
 
7.3%
o34
 
7.3%
l31
 
6.6%
n29
 
6.2%
b20
 
4.3%
c19
 
4.1%
Other values (20)99
21.2%
Uppercase Letter
ValueCountFrequency (%)
T56
24.2%
Q30
13.0%
Y24
10.4%
N15
 
6.5%
V15
 
6.5%
B13
 
5.6%
A12
 
5.2%
L12
 
5.2%
I11
 
4.8%
P8
 
3.5%
Other values (13)35
15.2%
Space Separator
ValueCountFrequency (%)
44
100.0%
Decimal Number
ValueCountFrequency (%)
22
100.0%
Math Symbol
ValueCountFrequency (%)
+1
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin690
92.4%
Common48
 
6.4%
Cyrillic9
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e72
 
10.4%
T56
 
8.1%
u45
 
6.5%
a45
 
6.5%
i40
 
5.8%
t34
 
4.9%
o34
 
4.9%
l31
 
4.5%
Q30
 
4.3%
n29
 
4.2%
Other values (36)274
39.7%
Cyrillic
ValueCountFrequency (%)
о2
22.2%
и2
22.2%
К1
11.1%
к1
11.1%
с1
11.1%
П1
11.1%
н1
11.1%
Common
ValueCountFrequency (%)
44
91.7%
22
 
4.2%
+1
 
2.1%
.1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII737
98.7%
Cyrillic9
 
1.2%
None1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e72
 
9.8%
T56
 
7.6%
u45
 
6.1%
a45
 
6.1%
44
 
6.0%
i40
 
5.4%
t34
 
4.6%
o34
 
4.6%
l31
 
4.2%
Q30
 
4.1%
Other values (39)306
41.5%
Cyrillic
ValueCountFrequency (%)
о2
22.2%
и2
22.2%
К1
11.1%
к1
11.1%
с1
11.1%
П1
11.1%
н1
11.1%
None
ValueCountFrequency (%)
é1
100.0%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing94
Missing (%)100.0%
Memory size880.0 B

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)25.9%
Missing40
Missing (%)42.6%
Memory size880.0 B
https://www.youtube.com
16 
https://v.qq.com/
13 
https://www.netflix.com/
10 
https://www.iq.com/
https://tv.naver.com/
Other values (9)

Length

Max length33
Median length30
Mean length21.87037037
Min length17

Characters and Unicode

Total characters1181
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)16.7%

Sample

1st rowhttps://www.youtube.com
2nd rowhttps://hd.kinopoisk.ru/
3rd rowhttps://v.qq.com/
4th rowhttps://www.seezntv.com/
5th rowhttps://tv.naver.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com16
 
17.0%
https://v.qq.com/13
 
13.8%
https://www.netflix.com/10
 
10.6%
https://www.iq.com/4
 
4.3%
https://tv.naver.com/2
 
2.1%
https://hd.kinopoisk.ru/1
 
1.1%
https://www.seezntv.com/1
 
1.1%
https://tv.kakao.com/top1
 
1.1%
http://www.wowpresentsplus.com1
 
1.1%
https://www.linetv.tw/1
 
1.1%
Other values (4)4
 
4.3%
(Missing)40
42.6%

Length

2022-09-05T21:47:08.063929image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com16
29.6%
https://v.qq.com13
24.1%
https://www.netflix.com10
18.5%
https://www.iq.com4
 
7.4%
https://tv.naver.com2
 
3.7%
https://hd.kinopoisk.ru1
 
1.9%
https://www.seezntv.com1
 
1.9%
https://tv.kakao.com/top1
 
1.9%
http://www.wowpresentsplus.com1
 
1.9%
https://www.linetv.tw1
 
1.9%
Other values (4)4
 
7.4%

Most occurring characters

ValueCountFrequency (%)
/145
12.3%
t144
12.2%
w111
 
9.4%
.109
 
9.2%
o76
 
6.4%
p62
 
5.2%
s62
 
5.2%
h57
 
4.8%
:54
 
4.6%
c53
 
4.5%
Other values (17)308
26.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter873
73.9%
Other Punctuation308
 
26.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t144
16.5%
w111
12.7%
o76
8.7%
p62
 
7.1%
s62
 
7.1%
h57
 
6.5%
c53
 
6.1%
m52
 
6.0%
u37
 
4.2%
e36
 
4.1%
Other values (14)183
21.0%
Other Punctuation
ValueCountFrequency (%)
/145
47.1%
.109
35.4%
:54
 
17.5%

Most occurring scripts

ValueCountFrequency (%)
Latin873
73.9%
Common308
 
26.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t144
16.5%
w111
12.7%
o76
8.7%
p62
 
7.1%
s62
 
7.1%
h57
 
6.5%
c53
 
6.1%
m52
 
6.0%
u37
 
4.2%
e36
 
4.1%
Other values (14)183
21.0%
Common
ValueCountFrequency (%)
/145
47.1%
.109
35.4%
:54
 
17.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1181
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/145
12.3%
t144
12.2%
w111
 
9.4%
.109
 
9.2%
o76
 
6.4%
p62
 
5.2%
s62
 
5.2%
h57
 
4.8%
:54
 
4.6%
c53
 
4.5%
Other values (17)308
26.1%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing94
Missing (%)100.0%
Memory size880.0 B

_embedded.show.externals.tvrage
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing93
Missing (%)98.9%
Memory size880.0 B
19056.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row19056.0

Common Values

ValueCountFrequency (%)
19056.01
 
1.1%
(Missing)93
98.9%

Length

2022-09-05T21:47:08.150525image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:08.226090image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
19056.01
100.0%

Most occurring characters

ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
85.7%
Other Punctuation1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02
33.3%
11
16.7%
91
16.7%
51
16.7%
61
16.7%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct42
Distinct (%)71.2%
Missing35
Missing (%)37.2%
Infinite0
Infinite (%)0.0%
Mean361846.8475
Minimum104271
Maximum419045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:08.308896image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum104271
5-th percentile273276.8
Q1366493.5
median383904
Q3392145
95-th percentile397247
Maximum419045
Range314774
Interquartile range (IQR)25651.5

Descriptive statistics

Standard deviation52860.55795
Coefficient of variation (CV)0.1460854456
Kurtosis8.86900168
Mean361846.8475
Median Absolute Deviation (MAD)9477
Skewness-2.60906146
Sum21348964
Variance2794238587
MonotonicityNot monotonic
2022-09-05T21:47:08.423615image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
38390411
 
11.7%
3865214
 
4.3%
3922142
 
2.1%
3972472
 
2.1%
3933812
 
2.1%
2787932
 
2.1%
3697981
 
1.1%
3885181
 
1.1%
3931741
 
1.1%
3920701
 
1.1%
Other values (32)32
34.0%
(Missing)35
37.2%
ValueCountFrequency (%)
1042711
1.1%
2604361
1.1%
2651931
1.1%
2741751
1.1%
2743991
1.1%
2787932
2.1%
2840461
1.1%
2906861
1.1%
3128331
1.1%
3213641
1.1%
ValueCountFrequency (%)
4190451
1.1%
3975831
1.1%
3972472
2.1%
3940871
1.1%
3940451
1.1%
3933812
2.1%
3933371
1.1%
3931741
1.1%
3926491
1.1%
3924551
1.1%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct25
Distinct (%)51.0%
Missing45
Missing (%)47.9%
Memory size880.0 B
tt11947358
11 
tt13530018
10 
tt12873702
tt13598988
 
2
tt1714810
 
2
Other values (20)
20 

Length

Max length10
Median length10
Mean length9.734693878
Min length9

Characters and Unicode

Total characters477
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)40.8%

Sample

1st rowtt13423446
2nd rowtt15127174
3rd rowtt11492320
4th rowtt11947358
5th rowtt11947358

Common Values

ValueCountFrequency (%)
tt1194735811
 
11.7%
tt1353001810
 
10.6%
tt128737024
 
4.3%
tt135989882
 
2.1%
tt17148102
 
2.1%
tt132805421
 
1.1%
tt106806141
 
1.1%
tt35893121
 
1.1%
tt02111591
 
1.1%
tt133403001
 
1.1%
Other values (15)15
 
16.0%
(Missing)45
47.9%

Length

2022-09-05T21:47:08.523260image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt1194735811
22.4%
tt1353001810
20.4%
tt128737024
 
8.2%
tt135989882
 
4.1%
tt17148102
 
4.1%
tt66189221
 
2.0%
tt151271741
 
2.0%
tt114923201
 
2.0%
tt107270441
 
2.0%
tt49071781
 
2.0%
Other values (15)15
30.6%

Most occurring characters

ValueCountFrequency (%)
t98
20.5%
179
16.6%
349
10.3%
049
10.3%
845
9.4%
734
 
7.1%
530
 
6.3%
429
 
6.1%
227
 
5.7%
926
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number379
79.5%
Lowercase Letter98
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
179
20.8%
349
12.9%
049
12.9%
845
11.9%
734
9.0%
530
 
7.9%
429
 
7.7%
227
 
7.1%
926
 
6.9%
611
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
t98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common379
79.5%
Latin98
 
20.5%

Most frequent character per script

Common
ValueCountFrequency (%)
179
20.8%
349
12.9%
049
12.9%
845
11.9%
734
9.0%
530
 
7.9%
429
 
7.7%
227
 
7.1%
926
 
6.9%
611
 
2.9%
Latin
ValueCountFrequency (%)
t98
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t98
20.5%
179
16.6%
349
10.3%
049
10.3%
845
9.4%
734
 
7.1%
530
 
6.3%
429
 
6.1%
227
 
5.7%
926
 
5.5%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct57
Distinct (%)62.6%
Missing3
Missing (%)3.2%
Memory size880.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/289/723510.jpg
11 
https://static.tvmaze.com/uploads/images/medium_portrait/383/959605.jpg
10 
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/294/735665.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg
 
3
Other values (52)
59 

Length

Max length72
Median length71
Mean length71
Min length70

Characters and Unicode

Total characters6461
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)49.5%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/277/693293.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/290/727378.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/289/723510.jpg11
 
11.7%
https://static.tvmaze.com/uploads/images/medium_portrait/383/959605.jpg10
 
10.6%
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg4
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/294/735665.jpg4
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg3
 
3.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/medium_portrait/261/653909.jpg2
 
2.1%
Other values (47)49
52.1%
(Missing)3
 
3.2%

Length

2022-09-05T21:47:08.627457image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/289/723510.jpg11
 
12.1%
https://static.tvmaze.com/uploads/images/medium_portrait/383/959605.jpg10
 
11.0%
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg4
 
4.4%
https://static.tvmaze.com/uploads/images/medium_portrait/294/735665.jpg4
 
4.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg3
 
3.3%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/261/653909.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.2%
Other values (47)49
53.8%

Most occurring characters

ValueCountFrequency (%)
t637
 
9.9%
/637
 
9.9%
m455
 
7.0%
a455
 
7.0%
p364
 
5.6%
s364
 
5.6%
i364
 
5.6%
o273
 
4.2%
.273
 
4.2%
e273
 
4.2%
Other values (22)2366
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4550
70.4%
Other Punctuation1001
 
15.5%
Decimal Number819
 
12.7%
Connector Punctuation91
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t637
14.0%
m455
10.0%
a455
10.0%
p364
 
8.0%
s364
 
8.0%
i364
 
8.0%
o273
 
6.0%
e273
 
6.0%
u182
 
4.0%
r182
 
4.0%
Other values (8)1001
22.0%
Decimal Number
ValueCountFrequency (%)
2108
13.2%
397
11.8%
595
11.6%
992
11.2%
889
10.9%
778
9.5%
076
9.3%
173
8.9%
660
7.3%
451
6.2%
Other Punctuation
ValueCountFrequency (%)
/637
63.6%
.273
27.3%
:91
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4550
70.4%
Common1911
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t637
14.0%
m455
10.0%
a455
10.0%
p364
 
8.0%
s364
 
8.0%
i364
 
8.0%
o273
 
6.0%
e273
 
6.0%
u182
 
4.0%
r182
 
4.0%
Other values (8)1001
22.0%
Common
ValueCountFrequency (%)
/637
33.3%
.273
14.3%
2108
 
5.7%
397
 
5.1%
595
 
5.0%
992
 
4.8%
_91
 
4.8%
:91
 
4.8%
889
 
4.7%
778
 
4.1%
Other values (4)260
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII6461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t637
 
9.9%
/637
 
9.9%
m455
 
7.0%
a455
 
7.0%
p364
 
5.6%
s364
 
5.6%
i364
 
5.6%
o273
 
4.2%
.273
 
4.2%
e273
 
4.2%
Other values (22)2366
36.6%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct57
Distinct (%)62.6%
Missing3
Missing (%)3.2%
Memory size880.0 B
https://static.tvmaze.com/uploads/images/original_untouched/289/723510.jpg
11 
https://static.tvmaze.com/uploads/images/original_untouched/383/959605.jpg
10 
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/294/735665.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg
 
3
Other values (52)
59 

Length

Max length75
Median length74
Mean length74
Min length73

Characters and Unicode

Total characters6734
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)49.5%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/277/693293.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/727378.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/289/723510.jpg11
 
11.7%
https://static.tvmaze.com/uploads/images/original_untouched/383/959605.jpg10
 
10.6%
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg4
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/294/735665.jpg4
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg3
 
3.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/original_untouched/261/653909.jpg2
 
2.1%
Other values (47)49
52.1%
(Missing)3
 
3.2%

Length

2022-09-05T21:47:08.735586image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/289/723510.jpg11
 
12.1%
https://static.tvmaze.com/uploads/images/original_untouched/383/959605.jpg10
 
11.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg4
 
4.4%
https://static.tvmaze.com/uploads/images/original_untouched/294/735665.jpg4
 
4.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg3
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/261/653909.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.2%
Other values (47)49
53.8%

Most occurring characters

ValueCountFrequency (%)
/637
 
9.5%
t546
 
8.1%
a455
 
6.8%
s364
 
5.4%
i364
 
5.4%
o364
 
5.4%
p273
 
4.1%
c273
 
4.1%
.273
 
4.1%
g273
 
4.1%
Other values (23)2912
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4823
71.6%
Other Punctuation1001
 
14.9%
Decimal Number819
 
12.2%
Connector Punctuation91
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t546
 
11.3%
a455
 
9.4%
s364
 
7.5%
i364
 
7.5%
o364
 
7.5%
p273
 
5.7%
c273
 
5.7%
g273
 
5.7%
m273
 
5.7%
e273
 
5.7%
Other values (9)1365
28.3%
Decimal Number
ValueCountFrequency (%)
2108
13.2%
397
11.8%
595
11.6%
992
11.2%
889
10.9%
778
9.5%
076
9.3%
173
8.9%
660
7.3%
451
6.2%
Other Punctuation
ValueCountFrequency (%)
/637
63.6%
.273
27.3%
:91
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4823
71.6%
Common1911
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t546
 
11.3%
a455
 
9.4%
s364
 
7.5%
i364
 
7.5%
o364
 
7.5%
p273
 
5.7%
c273
 
5.7%
g273
 
5.7%
m273
 
5.7%
e273
 
5.7%
Other values (9)1365
28.3%
Common
ValueCountFrequency (%)
/637
33.3%
.273
14.3%
2108
 
5.7%
397
 
5.1%
595
 
5.0%
992
 
4.8%
:91
 
4.8%
_91
 
4.8%
889
 
4.7%
778
 
4.1%
Other values (4)260
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII6734
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/637
 
9.5%
t546
 
8.1%
a455
 
6.8%
s364
 
5.4%
i364
 
5.4%
o364
 
5.4%
p273
 
4.1%
c273
 
4.1%
.273
 
4.1%
g273
 
4.1%
Other values (23)2912
43.2%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct54
Distinct (%)62.1%
Missing7
Missing (%)7.4%
Memory size880.0 B
<p>Don't teach your daddy how to make babies! Especially if your dad is Prem or Soggy, the daddy of all daddies in the daddy history! Who's Your Daddy is the tale of Prem, Soggy and Tidda, who'll tickle your funny bones as they go down their memory lanes laced with ‘blue-films' and hilarious sexual encounters to uncover who's the Daddy of Soggy's son!</p>
11 
<p>Love snackable, snap-worthy songs? Sing along with the Rhyme Time Town friends as they use their imaginations and flex their problem-solving skills!</p>
10 
<p>The play is set in the turbulent period of the Republic of China in Shanghai. In a turbulent era, the forensic doctor Che Suwei and the gentleman detective Gu Yuan are intertwined with various forces. "Deputy Inspector Kang Yichen, and the innocent and lively reporter Cao Qingluo worked together to crack out a number of weird and curious cases, and restore the truth.</p>
 
4
<p>Although Edgar Aquin can go unnoticed by his appearance, he is a formidable investigator, with an extraordinary sense of observation. With his unconventional methods, sharp instincts and unique logic, he will succeed in proving the guilt of the suspects every time!</p>
 
4
<p>Pan, a desolate plastic surgeon, lived a repetitive and boring life every day until a conspiracy happened. He woke up in an abandoned factory, and found that someone had replaced his identity with a face exactly like him. His world has been completely overturned and left in a perilous situation. Can he overcome the difficulties and peel away the truth? How would he regain his identity?</p>
 
3
Other values (49)
55 

Length

Max length1483
Median length541
Mean length330.6781609
Min length39

Characters and Unicode

Total characters28769
Distinct characters84
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)49.4%

Sample

1st row<p>Solo performances of stand-up comedians from the underground and popular TV and Internet projects. Each new release is a new concert with its own atmosphere and humor.</p>
2nd row<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>
3rd row<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>
4th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>
5th row<p>Da Eun works part-time and Kim Byul is an idol in her 5th years since debut. These two girls who look alike decide to change each other's lives just for 7 days. It tells the romantic encounters of these 2 girls.</p>

Common Values

ValueCountFrequency (%)
<p>Don't teach your daddy how to make babies! Especially if your dad is Prem or Soggy, the daddy of all daddies in the daddy history! Who's Your Daddy is the tale of Prem, Soggy and Tidda, who'll tickle your funny bones as they go down their memory lanes laced with ‘blue-films' and hilarious sexual encounters to uncover who's the Daddy of Soggy's son!</p>11
 
11.7%
<p>Love snackable, snap-worthy songs? Sing along with the Rhyme Time Town friends as they use their imaginations and flex their problem-solving skills!</p>10
 
10.6%
<p>The play is set in the turbulent period of the Republic of China in Shanghai. In a turbulent era, the forensic doctor Che Suwei and the gentleman detective Gu Yuan are intertwined with various forces. "Deputy Inspector Kang Yichen, and the innocent and lively reporter Cao Qingluo worked together to crack out a number of weird and curious cases, and restore the truth.</p>4
 
4.3%
<p>Although Edgar Aquin can go unnoticed by his appearance, he is a formidable investigator, with an extraordinary sense of observation. With his unconventional methods, sharp instincts and unique logic, he will succeed in proving the guilt of the suspects every time!</p>4
 
4.3%
<p>Pan, a desolate plastic surgeon, lived a repetitive and boring life every day until a conspiracy happened. He woke up in an abandoned factory, and found that someone had replaced his identity with a face exactly like him. His world has been completely overturned and left in a perilous situation. Can he overcome the difficulties and peel away the truth? How would he regain his identity?</p>3
 
3.2%
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>2
 
2.1%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
2.1%
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>2
 
2.1%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
2.1%
<p>Two unlikely individuals join forces to find the truth behind a series of murders using an unconventional method. Chen Si, a female detective with a sense of justice, unexpectedly becomess partners with Yuan Shuai, a dream interpreter with a dark past.</p>2
 
2.1%
Other values (44)45
47.9%
(Missing)7
 
7.4%

Length

2022-09-05T21:47:08.874473image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the307
 
6.4%
and175
 
3.7%
of137
 
2.9%
to115
 
2.4%
a103
 
2.2%
in91
 
1.9%
with73
 
1.5%
is63
 
1.3%
daddy55
 
1.2%
their51
 
1.1%
Other values (1375)3603
75.5%

Most occurring characters

ValueCountFrequency (%)
4675
16.3%
e2659
 
9.2%
t1768
 
6.1%
a1722
 
6.0%
o1690
 
5.9%
n1614
 
5.6%
i1558
 
5.4%
s1379
 
4.8%
r1304
 
4.5%
h1141
 
4.0%
Other values (74)9259
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter21713
75.5%
Space Separator4686
 
16.3%
Uppercase Letter918
 
3.2%
Other Punctuation836
 
2.9%
Math Symbol496
 
1.7%
Dash Punctuation69
 
0.2%
Decimal Number33
 
0.1%
Initial Punctuation11
 
< 0.1%
Close Punctuation3
 
< 0.1%
Open Punctuation3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2659
12.2%
t1768
 
8.1%
a1722
 
7.9%
o1690
 
7.8%
n1614
 
7.4%
i1558
 
7.2%
s1379
 
6.4%
r1304
 
6.0%
h1141
 
5.3%
d968
 
4.5%
Other values (19)5910
27.2%
Uppercase Letter
ValueCountFrequency (%)
T120
 
13.1%
S90
 
9.8%
D69
 
7.5%
A63
 
6.9%
Y52
 
5.7%
P48
 
5.2%
C46
 
5.0%
W43
 
4.7%
L39
 
4.2%
R38
 
4.1%
Other values (16)310
33.8%
Other Punctuation
ValueCountFrequency (%)
,275
32.9%
.195
23.3%
/128
15.3%
'116
13.9%
!59
 
7.1%
"27
 
3.2%
?18
 
2.2%
:13
 
1.6%
;3
 
0.4%
2
 
0.2%
Decimal Number
ValueCountFrequency (%)
011
33.3%
28
24.2%
15
15.2%
33
 
9.1%
52
 
6.1%
72
 
6.1%
81
 
3.0%
41
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
-60
87.0%
7
 
10.1%
2
 
2.9%
Space Separator
ValueCountFrequency (%)
4675
99.8%
 11
 
0.2%
Math Symbol
ValueCountFrequency (%)
<248
50.0%
>248
50.0%
Initial Punctuation
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin22631
78.7%
Common6138
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2659
 
11.7%
t1768
 
7.8%
a1722
 
7.6%
o1690
 
7.5%
n1614
 
7.1%
i1558
 
6.9%
s1379
 
6.1%
r1304
 
5.8%
h1141
 
5.0%
d968
 
4.3%
Other values (45)6828
30.2%
Common
ValueCountFrequency (%)
4675
76.2%
,275
 
4.5%
<248
 
4.0%
>248
 
4.0%
.195
 
3.2%
/128
 
2.1%
'116
 
1.9%
-60
 
1.0%
!59
 
1.0%
"27
 
0.4%
Other values (19)107
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII28732
99.9%
Punctuation22
 
0.1%
None15
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4675
16.3%
e2659
 
9.3%
t1768
 
6.2%
a1722
 
6.0%
o1690
 
5.9%
n1614
 
5.6%
i1558
 
5.4%
s1379
 
4.8%
r1304
 
4.5%
h1141
 
4.0%
Other values (66)9222
32.1%
Punctuation
ValueCountFrequency (%)
11
50.0%
7
31.8%
2
 
9.1%
2
 
9.1%
None
ValueCountFrequency (%)
 11
73.3%
é2
 
13.3%
è1
 
6.7%
å1
 
6.7%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct60
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1639929739
Minimum1604587119
Maximum1662380496
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2022-09-05T21:47:08.995577image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1604587119
5-th percentile1609369096
Q11619254319
median1645110771
Q31654000750
95-th percentile1661916033
Maximum1662380496
Range57793377
Interquartile range (IQR)34746430.75

Descriptive statistics

Standard deviation17934750.81
Coefficient of variation (CV)0.01093629219
Kurtosis-0.9602414959
Mean1639929739
Median Absolute Deviation (MAD)9334541
Skewness-0.6615369022
Sum1.541533955 × 1011
Variance3.216552865 × 1014
MonotonicityNot monotonic
2022-09-05T21:47:09.116876image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
164511077111
 
11.7%
163959266010
 
10.6%
16549760864
 
4.3%
16116133544
 
4.3%
16544453123
 
3.2%
16124781452
 
2.1%
16095351412
 
2.1%
16481900582
 
2.1%
16184666822
 
2.1%
16180767152
 
2.1%
Other values (50)52
55.3%
ValueCountFrequency (%)
16045871191
 
1.1%
16083529671
 
1.1%
16084062791
 
1.1%
16090607262
2.1%
16095351412
2.1%
16102192241
 
1.1%
16114368421
 
1.1%
16116133544
4.3%
16124781452
2.1%
16125776191
 
1.1%
ValueCountFrequency (%)
16623804961
1.1%
16623462771
1.1%
16622400131
1.1%
16619744211
1.1%
16619689571
1.1%
16618875351
1.1%
16615328091
1.1%
16615288411
1.1%
16614758321
1.1%
16614348681
1.1%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct60
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Memory size880.0 B
https://api.tvmaze.com/shows/52526
11 
https://api.tvmaze.com/shows/52629
10 
https://api.tvmaze.com/shows/52655
 
4
https://api.tvmaze.com/shows/53114
 
4
https://api.tvmaze.com/shows/52107
 
3
Other values (55)
62 

Length

Max length34
Median length34
Mean length33.9787234
Min length33

Characters and Unicode

Total characters3194
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)51.1%

Sample

1st rowhttps://api.tvmaze.com/shows/51065
2nd rowhttps://api.tvmaze.com/shows/52933
3rd rowhttps://api.tvmaze.com/shows/51336
4th rowhttps://api.tvmaze.com/shows/54033
5th rowhttps://api.tvmaze.com/shows/44276

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/5252611
 
11.7%
https://api.tvmaze.com/shows/5262910
 
10.6%
https://api.tvmaze.com/shows/526554
 
4.3%
https://api.tvmaze.com/shows/531144
 
4.3%
https://api.tvmaze.com/shows/521073
 
3.2%
https://api.tvmaze.com/shows/525242
 
2.1%
https://api.tvmaze.com/shows/521042
 
2.1%
https://api.tvmaze.com/shows/152502
 
2.1%
https://api.tvmaze.com/shows/547622
 
2.1%
https://api.tvmaze.com/shows/486732
 
2.1%
Other values (50)52
55.3%

Length

2022-09-05T21:47:09.214380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/5252611
 
11.7%
https://api.tvmaze.com/shows/5262910
 
10.6%
https://api.tvmaze.com/shows/526554
 
4.3%
https://api.tvmaze.com/shows/531144
 
4.3%
https://api.tvmaze.com/shows/521073
 
3.2%
https://api.tvmaze.com/shows/547622
 
2.1%
https://api.tvmaze.com/shows/524002
 
2.1%
https://api.tvmaze.com/shows/486732
 
2.1%
https://api.tvmaze.com/shows/521592
 
2.1%
https://api.tvmaze.com/shows/152502
 
2.1%
Other values (50)52
55.3%

Most occurring characters

ValueCountFrequency (%)
/376
 
11.8%
s282
 
8.8%
t282
 
8.8%
h188
 
5.9%
p188
 
5.9%
a188
 
5.9%
.188
 
5.9%
o188
 
5.9%
m188
 
5.9%
5104
 
3.3%
Other values (16)1022
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2068
64.7%
Other Punctuation658
 
20.6%
Decimal Number468
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s282
13.6%
t282
13.6%
h188
9.1%
p188
9.1%
a188
9.1%
o188
9.1%
m188
9.1%
e94
 
4.5%
w94
 
4.5%
c94
 
4.5%
Other values (3)282
13.6%
Decimal Number
ValueCountFrequency (%)
5104
22.2%
292
19.7%
652
11.1%
442
9.0%
140
 
8.5%
338
 
8.1%
032
 
6.8%
727
 
5.8%
924
 
5.1%
817
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/376
57.1%
.188
28.6%
:94
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2068
64.7%
Common1126
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/376
33.4%
.188
16.7%
5104
 
9.2%
:94
 
8.3%
292
 
8.2%
652
 
4.6%
442
 
3.7%
140
 
3.6%
338
 
3.4%
032
 
2.8%
Other values (3)68
 
6.0%
Latin
ValueCountFrequency (%)
s282
13.6%
t282
13.6%
h188
9.1%
p188
9.1%
a188
9.1%
o188
9.1%
m188
9.1%
e94
 
4.5%
w94
 
4.5%
c94
 
4.5%
Other values (3)282
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3194
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/376
 
11.8%
s282
 
8.8%
t282
 
8.8%
h188
 
5.9%
p188
 
5.9%
a188
 
5.9%
.188
 
5.9%
o188
 
5.9%
m188
 
5.9%
5104
 
3.3%
Other values (16)1022
32.0%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct60
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Memory size880.0 B
https://api.tvmaze.com/episodes/1990720
11 
https://api.tvmaze.com/episodes/1992681
10 
https://api.tvmaze.com/episodes/2340036
 
4
https://api.tvmaze.com/episodes/2015891
 
4
https://api.tvmaze.com/episodes/1976166
 
3
Other values (55)
62 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3666
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)51.1%

Sample

1st rowhttps://api.tvmaze.com/episodes/2007760
2nd rowhttps://api.tvmaze.com/episodes/2245512
3rd rowhttps://api.tvmaze.com/episodes/1964569
4th rowhttps://api.tvmaze.com/episodes/2309442
5th rowhttps://api.tvmaze.com/episodes/1993665

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/199072011
 
11.7%
https://api.tvmaze.com/episodes/199268110
 
10.6%
https://api.tvmaze.com/episodes/23400364
 
4.3%
https://api.tvmaze.com/episodes/20158914
 
4.3%
https://api.tvmaze.com/episodes/19761663
 
3.2%
https://api.tvmaze.com/episodes/19880792
 
2.1%
https://api.tvmaze.com/episodes/19760542
 
2.1%
https://api.tvmaze.com/episodes/23012762
 
2.1%
https://api.tvmaze.com/episodes/20714942
 
2.1%
https://api.tvmaze.com/episodes/20683632
 
2.1%
Other values (50)52
55.3%

Length

2022-09-05T21:47:09.299022image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/199072011
 
11.7%
https://api.tvmaze.com/episodes/199268110
 
10.6%
https://api.tvmaze.com/episodes/23400364
 
4.3%
https://api.tvmaze.com/episodes/20158914
 
4.3%
https://api.tvmaze.com/episodes/19761663
 
3.2%
https://api.tvmaze.com/episodes/20714942
 
2.1%
https://api.tvmaze.com/episodes/19849632
 
2.1%
https://api.tvmaze.com/episodes/20683632
 
2.1%
https://api.tvmaze.com/episodes/19776512
 
2.1%
https://api.tvmaze.com/episodes/23012762
 
2.1%
Other values (50)52
55.3%

Most occurring characters

ValueCountFrequency (%)
/376
 
10.3%
t282
 
7.7%
p282
 
7.7%
s282
 
7.7%
e282
 
7.7%
a188
 
5.1%
i188
 
5.1%
.188
 
5.1%
m188
 
5.1%
o188
 
5.1%
Other values (16)1222
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2350
64.1%
Other Punctuation658
 
17.9%
Decimal Number658
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t282
12.0%
p282
12.0%
s282
12.0%
e282
12.0%
a188
8.0%
i188
8.0%
m188
8.0%
o188
8.0%
h94
 
4.0%
d94
 
4.0%
Other values (3)282
12.0%
Decimal Number
ValueCountFrequency (%)
299
15.0%
993
14.1%
192
14.0%
081
12.3%
360
9.1%
757
8.7%
657
8.7%
856
8.5%
434
 
5.2%
529
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/376
57.1%
.188
28.6%
:94
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2350
64.1%
Common1316
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/376
28.6%
.188
14.3%
299
 
7.5%
:94
 
7.1%
993
 
7.1%
192
 
7.0%
081
 
6.2%
360
 
4.6%
757
 
4.3%
657
 
4.3%
Other values (3)119
 
9.0%
Latin
ValueCountFrequency (%)
t282
12.0%
p282
12.0%
s282
12.0%
e282
12.0%
a188
8.0%
i188
8.0%
m188
8.0%
o188
8.0%
h94
 
4.0%
d94
 
4.0%
Other values (3)282
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/376
 
10.3%
t282
 
7.7%
p282
 
7.7%
s282
 
7.7%
e282
 
7.7%
a188
 
5.1%
i188
 
5.1%
.188
 
5.1%
m188
 
5.1%
o188
 
5.1%
Other values (16)1222
33.3%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct25
Distinct (%)100.0%
Missing69
Missing (%)73.4%
Memory size880.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/294/737209.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/414/1037293.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/724613.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/403/1009868.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/724584.jpg
 
1
Other values (20)
20 

Length

Max length73
Median length72
Mean length72.12
Min length72

Characters and Unicode

Total characters1803
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/294/737209.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726356.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721861.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/725656.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/725622.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/294/737209.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/414/1037293.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724613.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/403/1009868.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724584.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/404/1012053.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725640.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/298/745538.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726704.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726703.jpg1
 
1.1%
Other values (15)15
 
16.0%
(Missing)69
73.4%

Length

2022-09-05T21:47:09.385675image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/294/737209.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726699.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726356.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721861.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725656.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725622.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725620.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724971.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726695.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726696.jpg1
 
4.0%
Other values (15)15
60.0%

Most occurring characters

ValueCountFrequency (%)
/175
 
9.7%
a150
 
8.3%
t125
 
6.9%
s125
 
6.9%
m125
 
6.9%
p100
 
5.5%
e100
 
5.5%
.75
 
4.2%
c75
 
4.2%
d75
 
4.2%
Other values (22)678
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1275
70.7%
Other Punctuation275
 
15.3%
Decimal Number228
 
12.6%
Connector Punctuation25
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a150
11.8%
t125
9.8%
s125
9.8%
m125
9.8%
p100
 
7.8%
e100
 
7.8%
c75
 
5.9%
d75
 
5.9%
i75
 
5.9%
g50
 
3.9%
Other values (8)275
21.6%
Decimal Number
ValueCountFrequency (%)
249
21.5%
732
14.0%
931
13.6%
031
13.6%
626
11.4%
414
 
6.1%
813
 
5.7%
111
 
4.8%
511
 
4.8%
310
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/175
63.6%
.75
27.3%
:25
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1275
70.7%
Common528
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a150
11.8%
t125
9.8%
s125
9.8%
m125
9.8%
p100
 
7.8%
e100
 
7.8%
c75
 
5.9%
d75
 
5.9%
i75
 
5.9%
g50
 
3.9%
Other values (8)275
21.6%
Common
ValueCountFrequency (%)
/175
33.1%
.75
14.2%
249
 
9.3%
732
 
6.1%
931
 
5.9%
031
 
5.9%
626
 
4.9%
_25
 
4.7%
:25
 
4.7%
414
 
2.7%
Other values (4)45
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1803
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/175
 
9.7%
a150
 
8.3%
t125
 
6.9%
s125
 
6.9%
m125
 
6.9%
p100
 
5.5%
e100
 
5.5%
.75
 
4.2%
c75
 
4.2%
d75
 
4.2%
Other values (22)678
37.6%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct25
Distinct (%)100.0%
Missing69
Missing (%)73.4%
Memory size880.0 B
https://static.tvmaze.com/uploads/images/original_untouched/294/737209.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/414/1037293.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/724613.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/403/1009868.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/724584.jpg
 
1
Other values (20)
20 

Length

Max length75
Median length74
Mean length74.12
Min length74

Characters and Unicode

Total characters1853
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/737209.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726356.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721861.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/725656.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/725622.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/294/737209.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/414/1037293.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/289/724613.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/403/1009868.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/289/724584.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/404/1012053.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/290/725640.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/298/745538.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/290/726704.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/290/726703.jpg1
 
1.1%
Other values (15)15
 
16.0%
(Missing)69
73.4%

Length

2022-09-05T21:47:09.474327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/294/737209.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726699.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726356.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/288/721861.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/725656.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/725622.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/725620.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/289/724971.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726695.jpg1
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726696.jpg1
 
4.0%
Other values (15)15
60.0%

Most occurring characters

ValueCountFrequency (%)
/175
 
9.4%
t150
 
8.1%
a125
 
6.7%
s100
 
5.4%
i100
 
5.4%
o100
 
5.4%
p75
 
4.0%
c75
 
4.0%
.75
 
4.0%
g75
 
4.0%
Other values (23)803
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1325
71.5%
Other Punctuation275
 
14.8%
Decimal Number228
 
12.3%
Connector Punctuation25
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t150
 
11.3%
a125
 
9.4%
s100
 
7.5%
i100
 
7.5%
o100
 
7.5%
p75
 
5.7%
c75
 
5.7%
g75
 
5.7%
m75
 
5.7%
e75
 
5.7%
Other values (9)375
28.3%
Decimal Number
ValueCountFrequency (%)
249
21.5%
732
14.0%
931
13.6%
031
13.6%
626
11.4%
414
 
6.1%
813
 
5.7%
111
 
4.8%
511
 
4.8%
310
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/175
63.6%
.75
27.3%
:25
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1325
71.5%
Common528
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t150
 
11.3%
a125
 
9.4%
s100
 
7.5%
i100
 
7.5%
o100
 
7.5%
p75
 
5.7%
c75
 
5.7%
g75
 
5.7%
m75
 
5.7%
e75
 
5.7%
Other values (9)375
28.3%
Common
ValueCountFrequency (%)
/175
33.1%
.75
14.2%
249
 
9.3%
732
 
6.1%
931
 
5.9%
031
 
5.9%
626
 
4.9%
:25
 
4.7%
_25
 
4.7%
414
 
2.7%
Other values (4)45
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1853
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/175
 
9.4%
t150
 
8.1%
a125
 
6.7%
s100
 
5.4%
i100
 
5.4%
o100
 
5.4%
p75
 
4.0%
c75
 
4.0%
.75
 
4.0%
g75
 
4.0%
Other values (23)803
43.3%

_embedded.show.network.id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing89
Missing (%)94.7%
Memory size880.0 B
308.0
159.0
205.0
1354.0
112.0

Length

Max length6
Median length5
Mean length5.2
Min length5

Characters and Unicode

Total characters26
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row308.0
2nd row159.0
3rd row205.0
4th row1354.0
5th row112.0

Common Values

ValueCountFrequency (%)
308.01
 
1.1%
159.01
 
1.1%
205.01
 
1.1%
1354.01
 
1.1%
112.01
 
1.1%
(Missing)89
94.7%

Length

2022-09-05T21:47:09.564214image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:09.662849image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
308.01
20.0%
159.01
20.0%
205.01
20.0%
1354.01
20.0%
112.01
20.0%

Most occurring characters

ValueCountFrequency (%)
07
26.9%
.5
19.2%
14
15.4%
53
11.5%
32
 
7.7%
22
 
7.7%
81
 
3.8%
91
 
3.8%
41
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number21
80.8%
Other Punctuation5
 
19.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
07
33.3%
14
19.0%
53
14.3%
32
 
9.5%
22
 
9.5%
81
 
4.8%
91
 
4.8%
41
 
4.8%
Other Punctuation
ValueCountFrequency (%)
.5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common26
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
07
26.9%
.5
19.2%
14
15.4%
53
11.5%
32
 
7.7%
22
 
7.7%
81
 
3.8%
91
 
3.8%
41
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
07
26.9%
.5
19.2%
14
15.4%
53
11.5%
32
 
7.7%
22
 
7.7%
81
 
3.8%
91
 
3.8%
41
 
3.8%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing89
Missing (%)94.7%
Memory size880.0 B
ТНТ
TBS
NFL Network
Fuji TV TWO
RTL4

Length

Max length11
Median length4
Mean length6.4
Min length3

Characters and Unicode

Total characters32
Distinct characters23
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowТНТ
2nd rowTBS
3rd rowNFL Network
4th rowFuji TV TWO
5th rowRTL4

Common Values

ValueCountFrequency (%)
ТНТ1
 
1.1%
TBS1
 
1.1%
NFL Network1
 
1.1%
Fuji TV TWO1
 
1.1%
RTL41
 
1.1%
(Missing)89
94.7%

Length

2022-09-05T21:47:09.757302image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:09.862079image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
тнт1
12.5%
tbs1
12.5%
nfl1
12.5%
network1
12.5%
fuji1
12.5%
tv1
12.5%
two1
12.5%
rtl41
12.5%

Most occurring characters

ValueCountFrequency (%)
T4
 
12.5%
3
 
9.4%
Т2
 
6.2%
N2
 
6.2%
F2
 
6.2%
L2
 
6.2%
k1
 
3.1%
R1
 
3.1%
O1
 
3.1%
W1
 
3.1%
Other values (13)13
40.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter19
59.4%
Lowercase Letter9
28.1%
Space Separator3
 
9.4%
Decimal Number1
 
3.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T4
21.1%
Т2
10.5%
N2
10.5%
F2
10.5%
L2
10.5%
R1
 
5.3%
O1
 
5.3%
W1
 
5.3%
V1
 
5.3%
Н1
 
5.3%
Other values (2)2
10.5%
Lowercase Letter
ValueCountFrequency (%)
k1
11.1%
i1
11.1%
j1
11.1%
u1
11.1%
w1
11.1%
r1
11.1%
o1
11.1%
t1
11.1%
e1
11.1%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin25
78.1%
Common4
 
12.5%
Cyrillic3
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
T4
16.0%
N2
 
8.0%
F2
 
8.0%
L2
 
8.0%
k1
 
4.0%
R1
 
4.0%
O1
 
4.0%
W1
 
4.0%
V1
 
4.0%
i1
 
4.0%
Other values (9)9
36.0%
Common
ValueCountFrequency (%)
3
75.0%
41
 
25.0%
Cyrillic
ValueCountFrequency (%)
Т2
66.7%
Н1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII29
90.6%
Cyrillic3
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T4
 
13.8%
3
 
10.3%
N2
 
6.9%
F2
 
6.9%
L2
 
6.9%
k1
 
3.4%
R1
 
3.4%
O1
 
3.4%
W1
 
3.4%
V1
 
3.4%
Other values (11)11
37.9%
Cyrillic
ValueCountFrequency (%)
Т2
66.7%
Н1
33.3%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)80.0%
Missing89
Missing (%)94.7%
Memory size880.0 B
Japan
Russian Federation
United States
Netherlands

Length

Max length18
Median length13
Mean length10.4
Min length5

Characters and Unicode

Total characters52
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st rowRussian Federation
2nd rowJapan
3rd rowUnited States
4th rowJapan
5th rowNetherlands

Common Values

ValueCountFrequency (%)
Japan2
 
2.1%
Russian Federation1
 
1.1%
United States1
 
1.1%
Netherlands1
 
1.1%
(Missing)89
94.7%

Length

2022-09-05T21:47:09.957862image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:10.051628image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
japan2
28.6%
russian1
14.3%
federation1
14.3%
united1
14.3%
states1
14.3%
netherlands1
14.3%

Most occurring characters

ValueCountFrequency (%)
a8
15.4%
e6
11.5%
n6
11.5%
t5
9.6%
s4
 
7.7%
d3
 
5.8%
i3
 
5.8%
r2
 
3.8%
J2
 
3.8%
2
 
3.8%
Other values (10)11
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter43
82.7%
Uppercase Letter7
 
13.5%
Space Separator2
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a8
18.6%
e6
14.0%
n6
14.0%
t5
11.6%
s4
9.3%
d3
 
7.0%
i3
 
7.0%
r2
 
4.7%
p2
 
4.7%
u1
 
2.3%
Other values (3)3
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
J2
28.6%
F1
14.3%
R1
14.3%
U1
14.3%
S1
14.3%
N1
14.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin50
96.2%
Common2
 
3.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a8
16.0%
e6
12.0%
n6
12.0%
t5
10.0%
s4
8.0%
d3
 
6.0%
i3
 
6.0%
r2
 
4.0%
J2
 
4.0%
p2
 
4.0%
Other values (9)9
18.0%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII52
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a8
15.4%
e6
11.5%
n6
11.5%
t5
9.6%
s4
 
7.7%
d3
 
5.8%
i3
 
5.8%
r2
 
3.8%
J2
 
3.8%
2
 
3.8%
Other values (10)11
21.2%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)80.0%
Missing89
Missing (%)94.7%
Memory size880.0 B
JP
RU
US
NL

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st rowRU
2nd rowJP
3rd rowUS
4th rowJP
5th rowNL

Common Values

ValueCountFrequency (%)
JP2
 
2.1%
RU1
 
1.1%
US1
 
1.1%
NL1
 
1.1%
(Missing)89
94.7%

Length

2022-09-05T21:47:10.134746image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:10.221390image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
jp2
40.0%
ru1
20.0%
us1
20.0%
nl1
20.0%

Most occurring characters

ValueCountFrequency (%)
J2
20.0%
P2
20.0%
U2
20.0%
R1
10.0%
S1
10.0%
N1
10.0%
L1
10.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter10
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
J2
20.0%
P2
20.0%
U2
20.0%
R1
10.0%
S1
10.0%
N1
10.0%
L1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
J2
20.0%
P2
20.0%
U2
20.0%
R1
10.0%
S1
10.0%
N1
10.0%
L1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
J2
20.0%
P2
20.0%
U2
20.0%
R1
10.0%
S1
10.0%
N1
10.0%
L1
10.0%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)80.0%
Missing89
Missing (%)94.7%
Memory size880.0 B
Asia/Tokyo
Asia/Kamchatka
America/New_York
Europe/Amsterdam

Length

Max length16
Median length14
Mean length13.2
Min length10

Characters and Unicode

Total characters66
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Tokyo
3rd rowAmerica/New_York
4th rowAsia/Tokyo
5th rowEurope/Amsterdam

Common Values

ValueCountFrequency (%)
Asia/Tokyo2
 
2.1%
Asia/Kamchatka1
 
1.1%
America/New_York1
 
1.1%
Europe/Amsterdam1
 
1.1%
(Missing)89
94.7%

Length

2022-09-05T21:47:10.308217image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:10.402428image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/tokyo2
40.0%
asia/kamchatka1
20.0%
america/new_york1
20.0%
europe/amsterdam1
20.0%

Most occurring characters

ValueCountFrequency (%)
a8
12.1%
o6
 
9.1%
A5
 
7.6%
/5
 
7.6%
r4
 
6.1%
i4
 
6.1%
k4
 
6.1%
m4
 
6.1%
s4
 
6.1%
e4
 
6.1%
Other values (14)18
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter49
74.2%
Uppercase Letter11
 
16.7%
Other Punctuation5
 
7.6%
Connector Punctuation1
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a8
16.3%
o6
12.2%
r4
8.2%
i4
8.2%
k4
8.2%
m4
8.2%
s4
8.2%
e4
8.2%
y2
 
4.1%
c2
 
4.1%
Other values (6)7
14.3%
Uppercase Letter
ValueCountFrequency (%)
A5
45.5%
T2
 
18.2%
Y1
 
9.1%
E1
 
9.1%
N1
 
9.1%
K1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
/5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin60
90.9%
Common6
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a8
13.3%
o6
 
10.0%
A5
 
8.3%
r4
 
6.7%
i4
 
6.7%
k4
 
6.7%
m4
 
6.7%
s4
 
6.7%
e4
 
6.7%
T2
 
3.3%
Other values (12)15
25.0%
Common
ValueCountFrequency (%)
/5
83.3%
_1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a8
12.1%
o6
 
9.1%
A5
 
7.6%
/5
 
7.6%
r4
 
6.1%
i4
 
6.1%
k4
 
6.1%
m4
 
6.1%
s4
 
6.1%
e4
 
6.1%
Other values (14)18
27.3%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing94
Missing (%)100.0%
Memory size880.0 B

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)20.8%
Missing41
Missing (%)43.6%
Memory size880.0 B
China
19 
India
11 
Korea, Republic of
Canada
United States
Other values (6)
11 

Length

Max length25
Median length5
Mean length8.018867925
Min length5

Characters and Unicode

Total characters425
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.7%

Sample

1st rowRussian Federation
2nd rowChina
3rd rowChina
4th rowKorea, Republic of
5th rowKorea, Republic of

Common Values

ValueCountFrequency (%)
China19
20.2%
India11
 
11.7%
Korea, Republic of4
 
4.3%
Canada4
 
4.3%
United States4
 
4.3%
Japan3
 
3.2%
Norway3
 
3.2%
Russian Federation2
 
2.1%
Taiwan, Province of China1
 
1.1%
Iran, Islamic Republic of1
 
1.1%
(Missing)41
43.6%

Length

2022-09-05T21:47:10.509126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china20
27.4%
india11
15.1%
of6
 
8.2%
republic5
 
6.8%
korea4
 
5.5%
canada4
 
5.5%
united4
 
5.5%
states4
 
5.5%
norway3
 
4.1%
japan3
 
4.1%
Other values (7)9
12.3%

Most occurring characters

ValueCountFrequency (%)
a70
16.5%
n50
11.8%
i48
11.3%
C24
 
5.6%
d22
 
5.2%
e22
 
5.2%
h21
 
4.9%
20
 
4.7%
o16
 
3.8%
t14
 
3.3%
Other values (23)118
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter332
78.1%
Uppercase Letter67
 
15.8%
Space Separator20
 
4.7%
Other Punctuation6
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a70
21.1%
n50
15.1%
i48
14.5%
d22
 
6.6%
e22
 
6.6%
h21
 
6.3%
o16
 
4.8%
t14
 
4.2%
r11
 
3.3%
s9
 
2.7%
Other values (10)49
14.8%
Uppercase Letter
ValueCountFrequency (%)
C24
35.8%
I13
19.4%
R7
 
10.4%
U4
 
6.0%
S4
 
6.0%
K4
 
6.0%
J3
 
4.5%
N3
 
4.5%
F2
 
3.0%
T2
 
3.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Punctuation
ValueCountFrequency (%)
,6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin399
93.9%
Common26
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a70
17.5%
n50
12.5%
i48
12.0%
C24
 
6.0%
d22
 
5.5%
e22
 
5.5%
h21
 
5.3%
o16
 
4.0%
t14
 
3.5%
I13
 
3.3%
Other values (21)99
24.8%
Common
ValueCountFrequency (%)
20
76.9%
,6
 
23.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII425
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a70
16.5%
n50
11.8%
i48
11.3%
C24
 
5.6%
d22
 
5.2%
e22
 
5.2%
h21
 
4.9%
20
 
4.7%
o16
 
3.8%
t14
 
3.3%
Other values (23)118
27.8%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)20.8%
Missing41
Missing (%)43.6%
Memory size880.0 B
CN
19 
IN
11 
KR
CA
US
Other values (6)
11 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters106
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.7%

Sample

1st rowRU
2nd rowCN
3rd rowCN
4th rowKR
5th rowKR

Common Values

ValueCountFrequency (%)
CN19
20.2%
IN11
 
11.7%
KR4
 
4.3%
CA4
 
4.3%
US4
 
4.3%
JP3
 
3.2%
NO3
 
3.2%
RU2
 
2.1%
TW1
 
1.1%
IR1
 
1.1%
(Missing)41
43.6%

Length

2022-09-05T21:47:10.606544image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn19
35.8%
in11
20.8%
kr4
 
7.5%
ca4
 
7.5%
us4
 
7.5%
jp3
 
5.7%
no3
 
5.7%
ru2
 
3.8%
tw1
 
1.9%
ir1
 
1.9%

Most occurring characters

ValueCountFrequency (%)
N33
31.1%
C23
21.7%
I12
 
11.3%
R7
 
6.6%
U6
 
5.7%
K4
 
3.8%
A4
 
3.8%
S4
 
3.8%
J3
 
2.8%
P3
 
2.8%
Other values (4)7
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter106
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N33
31.1%
C23
21.7%
I12
 
11.3%
R7
 
6.6%
U6
 
5.7%
K4
 
3.8%
A4
 
3.8%
S4
 
3.8%
J3
 
2.8%
P3
 
2.8%
Other values (4)7
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
Latin106
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N33
31.1%
C23
21.7%
I12
 
11.3%
R7
 
6.6%
U6
 
5.7%
K4
 
3.8%
A4
 
3.8%
S4
 
3.8%
J3
 
2.8%
P3
 
2.8%
Other values (4)7
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N33
31.1%
C23
21.7%
I12
 
11.3%
R7
 
6.6%
U6
 
5.7%
K4
 
3.8%
A4
 
3.8%
S4
 
3.8%
J3
 
2.8%
P3
 
2.8%
Other values (4)7
 
6.6%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)20.8%
Missing41
Missing (%)43.6%
Memory size880.0 B
Asia/Shanghai
19 
Asia/Kolkata
11 
Asia/Seoul
America/Halifax
America/New_York
Other values (6)
11 

Length

Max length16
Median length15
Mean length12.60377358
Min length10

Characters and Unicode

Total characters668
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.7%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Shanghai
3rd rowAsia/Shanghai
4th rowAsia/Seoul
5th rowAsia/Seoul

Common Values

ValueCountFrequency (%)
Asia/Shanghai19
20.2%
Asia/Kolkata11
 
11.7%
Asia/Seoul4
 
4.3%
America/Halifax4
 
4.3%
America/New_York4
 
4.3%
Asia/Tokyo3
 
3.2%
Europe/Oslo3
 
3.2%
Asia/Kamchatka2
 
2.1%
Asia/Taipei1
 
1.1%
Asia/Tehran1
 
1.1%
(Missing)41
43.6%

Length

2022-09-05T21:47:10.703560image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai19
35.8%
asia/kolkata11
20.8%
asia/seoul4
 
7.5%
america/halifax4
 
7.5%
america/new_york4
 
7.5%
asia/tokyo3
 
5.7%
europe/oslo3
 
5.7%
asia/kamchatka2
 
3.8%
asia/taipei1
 
1.9%
asia/tehran1
 
1.9%

Most occurring characters

ValueCountFrequency (%)
a127
19.0%
i75
11.2%
/53
 
7.9%
A50
 
7.5%
s45
 
6.7%
h41
 
6.1%
o32
 
4.8%
S23
 
3.4%
l22
 
3.3%
k22
 
3.3%
Other values (22)178
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter501
75.0%
Uppercase Letter110
 
16.5%
Other Punctuation53
 
7.9%
Connector Punctuation4
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a127
25.3%
i75
15.0%
s45
 
9.0%
h41
 
8.2%
o32
 
6.4%
l22
 
4.4%
k22
 
4.4%
n21
 
4.2%
e21
 
4.2%
g20
 
4.0%
Other values (10)75
15.0%
Uppercase Letter
ValueCountFrequency (%)
A50
45.5%
S23
20.9%
K13
 
11.8%
T5
 
4.5%
H4
 
3.6%
N4
 
3.6%
Y4
 
3.6%
E3
 
2.7%
O3
 
2.7%
B1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/53
100.0%
Connector Punctuation
ValueCountFrequency (%)
_4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin611
91.5%
Common57
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a127
20.8%
i75
12.3%
A50
 
8.2%
s45
 
7.4%
h41
 
6.7%
o32
 
5.2%
S23
 
3.8%
l22
 
3.6%
k22
 
3.6%
n21
 
3.4%
Other values (20)153
25.0%
Common
ValueCountFrequency (%)
/53
93.0%
_4
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII668
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a127
19.0%
i75
11.2%
/53
 
7.9%
A50
 
7.5%
s45
 
6.7%
h41
 
6.1%
o32
 
4.8%
S23
 
3.4%
l22
 
3.3%
k22
 
3.3%
Other values (22)178
26.6%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing88
Missing (%)93.6%
Memory size880.0 B
https://api.tvmaze.com/episodes/2309443
https://api.tvmaze.com/episodes/2376729
https://api.tvmaze.com/episodes/2375640
https://api.tvmaze.com/episodes/2383184
https://api.tvmaze.com/episodes/2383145

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters234
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2309443
2nd rowhttps://api.tvmaze.com/episodes/2376729
3rd rowhttps://api.tvmaze.com/episodes/2375640
4th rowhttps://api.tvmaze.com/episodes/2383184
5th rowhttps://api.tvmaze.com/episodes/2383145

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094431
 
1.1%
https://api.tvmaze.com/episodes/23767291
 
1.1%
https://api.tvmaze.com/episodes/23756401
 
1.1%
https://api.tvmaze.com/episodes/23831841
 
1.1%
https://api.tvmaze.com/episodes/23831451
 
1.1%
https://api.tvmaze.com/episodes/23797031
 
1.1%
(Missing)88
93.6%

Length

2022-09-05T21:47:10.793586image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:10.892906image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094431
16.7%
https://api.tvmaze.com/episodes/23767291
16.7%
https://api.tvmaze.com/episodes/23756401
16.7%
https://api.tvmaze.com/episodes/23831841
16.7%
https://api.tvmaze.com/episodes/23831451
16.7%
https://api.tvmaze.com/episodes/23797031
16.7%

Most occurring characters

ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
o12
 
5.1%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
Other values (16)78
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter150
64.1%
Other Punctuation42
 
17.9%
Decimal Number42
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
o12
8.0%
a12
8.0%
i12
8.0%
m12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%
Decimal Number
ValueCountFrequency (%)
310
23.8%
27
16.7%
45
11.9%
75
11.9%
03
 
7.1%
93
 
7.1%
83
 
7.1%
62
 
4.8%
52
 
4.8%
12
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/24
57.1%
.12
28.6%
:6
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin150
64.1%
Common84
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/24
28.6%
.12
14.3%
310
11.9%
27
 
8.3%
:6
 
7.1%
45
 
6.0%
75
 
6.0%
03
 
3.6%
93
 
3.6%
83
 
3.6%
Other values (3)6
 
7.1%
Latin
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
o12
8.0%
a12
8.0%
i12
8.0%
m12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
o12
 
5.1%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
Other values (16)78
33.3%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing94
Missing (%)100.0%
Memory size880.0 B

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing94
Missing (%)100.0%
Memory size880.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing93
Missing (%)98.9%
Memory size880.0 B
Japan

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowJapan

Common Values

ValueCountFrequency (%)
Japan1
 
1.1%
(Missing)93
98.9%

Length

2022-09-05T21:47:10.985534image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:11.062527image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
japan1
100.0%

Most occurring characters

ValueCountFrequency (%)
a2
40.0%
J1
20.0%
p1
20.0%
n1
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4
80.0%
Uppercase Letter1
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a2
50.0%
p1
25.0%
n1
25.0%
Uppercase Letter
ValueCountFrequency (%)
J1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a2
40.0%
J1
20.0%
p1
20.0%
n1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a2
40.0%
J1
20.0%
p1
20.0%
n1
20.0%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing93
Missing (%)98.9%
Memory size880.0 B
JP

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowJP

Common Values

ValueCountFrequency (%)
JP1
 
1.1%
(Missing)93
98.9%

Length

2022-09-05T21:47:11.140420image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:11.219774image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
jp1
100.0%

Most occurring characters

ValueCountFrequency (%)
J1
50.0%
P1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
J1
50.0%
P1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
J1
50.0%
P1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
J1
50.0%
P1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing93
Missing (%)98.9%
Memory size880.0 B
Asia/Tokyo

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsia/Tokyo

Common Values

ValueCountFrequency (%)
Asia/Tokyo1
 
1.1%
(Missing)93
98.9%

Length

2022-09-05T21:47:11.292650image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:47:11.370663image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/tokyo1
100.0%

Most occurring characters

ValueCountFrequency (%)
o2
20.0%
A1
10.0%
s1
10.0%
i1
10.0%
a1
10.0%
/1
10.0%
T1
10.0%
k1
10.0%
y1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7
70.0%
Uppercase Letter2
 
20.0%
Other Punctuation1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2
28.6%
s1
14.3%
i1
14.3%
a1
14.3%
k1
14.3%
y1
14.3%
Uppercase Letter
ValueCountFrequency (%)
A1
50.0%
T1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9
90.0%
Common1
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2
22.2%
A1
11.1%
s1
11.1%
i1
11.1%
a1
11.1%
T1
11.1%
k1
11.1%
y1
11.1%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2
20.0%
A1
10.0%
s1
10.0%
i1
10.0%
a1
10.0%
/1
10.0%
T1
10.0%
k1
10.0%
y1
10.0%

Interactions

2022-09-05T21:47:01.229592image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:53.576620image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.404286image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.175955image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.939503image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.675654image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.429251image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.232903image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.994218image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.712553image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.454694image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.299046image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:53.748839image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.469260image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.247055image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.002634image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.740380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.492659image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.301685image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.055152image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.776388image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.520748image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.369514image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:53.822419image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.544643image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.319483image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.072457image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.811947image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.569023image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.373125image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.125084image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.845322image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.594527image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.439407image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:53.888169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.615585image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.389434image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.142802image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.880495image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.653391image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.442865image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.194755image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.912483image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.669394image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.511264image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:53.952744image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.683775image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.460890image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.209350image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.951332image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.727890image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.514686image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.259204image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.983004image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.737763image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.582299image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.020932image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.753051image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.528815image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.275527image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.019439image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.799544image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.581968image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.323360image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.049329image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.804713image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.658689image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.085413image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.827588image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.594876image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.341296image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.086115image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.875116image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.654896image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.387362image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.114858image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.882215image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.734514image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.149552image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.896749image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.668976image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.411347image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.159523image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.949335image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.727164image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.454407image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.185188image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.950471image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.803249image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.209806image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.962574image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.732853image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.475214image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.223616image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.018844image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.790096image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.515612image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.250887image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.014833image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.887687image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.272886image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.033874image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.798739image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.539481image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.287795image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.093069image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.855163image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.578551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.313958image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.088112image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.963230image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:54.341465image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.106083image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:55.870736image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:56.605922image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:57.360310image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.166003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:58.926697image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:59.643236image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:00.388174image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:01.157689image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:47:11.461891image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:47:11.725982image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:47:11.961492image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:47:12.249864image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:47:02.346143image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:47:03.090692image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:47:03.601940image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show._links.nextepisode.href_embedded.show.image_embedded.show.webChannel_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
02007750https://www.tvmaze.com/episodes/2007750/stand-up-autsajd-1x10-filipp-voronin-499-iz-5Филипп Воронин "4,99 из 5"110.0regular2020-12-2212:002020-12-22T00:00:00+00:0029.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200775051065https://www.tvmaze.com/shows/51065/stand-up-autsajdStand Up АутсайдVarietyRussian[]Ended40.028.02020-10-132020-12-31https://premier.one/show/13734[Monday]NaN4NaN21.0YouTubeNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/277/693293.jpghttps://static.tvmaze.com/uploads/images/original_untouched/277/693293.jpg<p>Solo performances of stand-up comedians from the underground and popular TV and Internet projects. Each new release is a new concert with its own atmosphere and humor.</p>1616719192https://api.tvmaze.com/shows/51065https://api.tvmaze.com/episodes/2007760NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
12008030https://www.tvmaze.com/episodes/2008030/lab-s-antonom-belaevym-2x09-gruppa-skryptoniteGruppa Skryptonite29.0regular2020-12-222020-12-22T00:00:00+00:0032.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200803052933https://www.tvmaze.com/shows/52933/lab-s-antonom-belaevymLAB с Антоном БеляевымDocumentaryRussian[Music]To Be Determined26.025.02019-12-17Nonehttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva23:45[Saturday]NaN25NaN381.0КиноПоиск HDNaNhttps://hd.kinopoisk.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpghttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>1654035738https://api.tvmaze.com/shows/52933https://api.tvmaze.com/episodes/2245512https://static.tvmaze.com/uploads/images/medium_landscape/294/737209.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/737209.jpg308.0ТНТRussian FederationRUAsia/KamchatkaNaNRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaN
21964568https://www.tvmaze.com/episodes/1964568/core-sense-1x12-episode-12Episode 12112.0regular2020-12-2210:002020-12-22T02:00:00+00:0024.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196456851336https://www.tvmaze.com/shows/51336/core-senseCore SenseAnimationChinese[Action, Anime, Science-Fiction]Running24.024.02020-10-13Nonehttps://www.bilibili.com/bangumi/media/md2822306410:00[Tuesday]NaN29NaN51.0BilibiliNaNNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpghttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>1604587119https://api.tvmaze.com/shows/51336https://api.tvmaze.com/episodes/1964569NaNNaNNaNNaNNaNNaNNaNNaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaN
32052511https://www.tvmaze.com/episodes/2052511/wu-shen-zhu-zai-1x86-episode-86Episode 86186.0regular2020-12-2210:002020-12-22T02:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/205251154033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese[Action, Adventure, Anime, Fantasy]Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html10:00[Tuesday, Sunday]NaN82NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN379070.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1649423444https://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309442NaNNaNNaNNaNNaNNaNNaNNaNChinaCNAsia/Shanghaihttps://api.tvmaze.com/episodes/2309443NaNNaNNaNNaNNaN
41993656https://www.tvmaze.com/episodes/1993656/7-days-of-romance-2x01-episode-1Episode 121.0regular2020-12-222020-12-22T03:00:00+00:0015.0NaNNoneNaNhttps://api.tvmaze.com/episodes/199365644276https://www.tvmaze.com/shows/44276/7-days-of-romance7 Days of RomanceScriptedKorean[Drama, Romance]EndedNaN15.02019-10-082021-01-20None[Tuesday, Wednesday]NaN81NaN380.0SeeznNaNhttps://www.seezntv.com/NaNNaN370873.0tt13423446https://static.tvmaze.com/uploads/images/medium_portrait/290/727378.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/727378.jpg<p>Da Eun works part-time and Kim Byul is an idol in her 5th years since debut. These two girls who look alike decide to change each other's lives just for 7 days. It tells the romantic encounters of these 2 girls.</p>1650033745https://api.tvmaze.com/shows/44276https://api.tvmaze.com/episodes/1993665NaNNaNNaNNaNNaNNaNNaNNaNKorea, Republic ofKRAsia/SeoulNaNNaNNaNNaNNaNNaN
52096299https://www.tvmaze.com/episodes/2096299/no-turning-back-romance-1x05-5515.0regular2020-12-222020-12-22T03:00:00+00:0012.0NaNNoneNaNhttps://api.tvmaze.com/episodes/209629955002https://www.tvmaze.com/shows/55002/no-turning-back-romanceNo Turning Back RomanceScriptedKorean[]EndedNaN12.02020-12-082021-01-06None[Tuesday, Wednesday]NaN23NaN30.0Naver TVCastNaNhttps://tv.naver.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/319/799196.jpghttps://static.tvmaze.com/uploads/images/original_untouched/319/799196.jpg<p>A teen romance of So Dam, a sixteen-year-old girl, who has never dated before but she receives her first-ever love confession from a mysterious boy. She is looking for the boy who secretly confessed to her while she was asleep on her desk. The clues include a male voice, mango fruit scent and gym uniform. She must piece the puzzle to find that person among the likely candidates that include hot shots Park Ji Hoo, Jeong Han Kyul, and Joo In Hyuk.</p>1621617231https://api.tvmaze.com/shows/55002https://api.tvmaze.com/episodes/2096309NaNNaNNaNNaNNaNNaNNaNNaNKorea, Republic ofKRAsia/SeoulNaNNaNNaNNaNNaNNaN
62315117https://www.tvmaze.com/episodes/2315117/sono-koi-mousukoshi-atatamemasuka-1x06-episode-6Episode 616.0regular2020-12-222020-12-22T03:00:00+00:0015.0NaNNoneNaNhttps://api.tvmaze.com/episodes/231511761674https://www.tvmaze.com/shows/61674/sono-koi-mousukoshi-atatamemasukaSono koi Mousukoshi AtatamemasukaScriptedJapanese[Romance]Ended15.015.02020-10-202020-12-22https://www.paravi.jp/static/koisuko22:00[Tuesday]NaN1NaN342.0ParaviNaNNoneNaNNaN419045.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/404/1012331.jpghttps://static.tvmaze.com/uploads/images/original_untouched/404/1012331.jpg<p>It's spin-off drama of <b>"Kono Koi Atatamemasu ka"</b></p>1650915213https://api.tvmaze.com/shows/61674https://api.tvmaze.com/episodes/2315117NaNNaNNaNNaNNaNNaNNaNNaNJapanJPAsia/TokyoNaNNaNNaNNaNNaNNaN
72068349https://www.tvmaze.com/episodes/2068349/doomsday-awakening-2x01-episode-1Episode 121.0regular2020-12-222020-12-22T04:00:00+00:0015.0NaNNoneNaNhttps://api.tvmaze.com/episodes/206834948673https://www.tvmaze.com/shows/48673/doomsday-awakeningDoomsday AwakeningAnimationChinese[Action, Anime, Science-Fiction, War]Running15.015.02018-05-24Nonehttps://v.qq.com/detail/j/jaqpncskrgv28oo.html[Tuesday]NaN75NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/261/653909.jpghttps://static.tvmaze.com/uploads/images/original_untouched/261/653909.jpgNone1618076715https://api.tvmaze.com/shows/48673https://api.tvmaze.com/episodes/2068363NaNNaNNaNNaNNaNNaNNaNNaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaN
82068351https://www.tvmaze.com/episodes/2068351/doomsday-awakening-2x02-episode-2Episode 222.0regular2020-12-222020-12-22T04:00:00+00:0015.0NaNNoneNaNhttps://api.tvmaze.com/episodes/206835148673https://www.tvmaze.com/shows/48673/doomsday-awakeningDoomsday AwakeningAnimationChinese[Action, Anime, Science-Fiction, War]Running15.015.02018-05-24Nonehttps://v.qq.com/detail/j/jaqpncskrgv28oo.html[Tuesday]NaN75NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/261/653909.jpghttps://static.tvmaze.com/uploads/images/original_untouched/261/653909.jpgNone1618076715https://api.tvmaze.com/shows/48673https://api.tvmaze.com/episodes/2068363NaNNaNNaNNaNNaNNaNNaNNaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaN
92005750https://www.tvmaze.com/episodes/2005750/legend-of-yun-qian-1x03-episode-3Episode 313.0regular2020-12-222020-12-22T04:00:00+00:004.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200575052898https://www.tvmaze.com/shows/52898/legend-of-yun-qianLegend of Yun QianScriptedChinese[Drama, Romance, History]Ended4.04.02020-12-212020-12-31None19:00[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN23NaN445.0CTI TVNaNNoneNaNNaN394087.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/292/731348.jpghttps://static.tvmaze.com/uploads/images/original_untouched/292/731348.jpg<p>The disciples of the Lingchuan Sect have guarded the Fans of Heaven and Earth for nearly a century. Mu Yun and Hua Yue are the only disciples of the sect that are left. The stubborn and disobedient Hua Yue unintentionally discovers that the Fan of Heaven possesses the power to travel through time. To escape being forced to study and practice martial arts by Mu Yun, Hua Yue travels to the future to have fun. Hundreds of years in the future she meets Xiao Qian who looks exactly like her. Secrets come to the surface, and adventures take place.</p>1649956202https://api.tvmaze.com/shows/52898https://api.tvmaze.com/episodes/2005762NaNNaNNaNNaNNaNNaNNaNNaNTaiwan, Province of ChinaTWAsia/TaipeiNaNNaNNaNNaNNaNNaN

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show._links.nextepisode.href_embedded.show.image_embedded.show.webChannel_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
842311020https://www.tvmaze.com/episodes/2311020/toki-wo-kakeru-bando-1x10-band-that-takes-timeBand that takes time110.0regular2020-12-2200:252020-12-22T15:25:00+00:0027.0NaN<p>'Ryo', who broke up with 'Chahan', 'Yuki Ehana,' 'Shiori Kato,' and 'Hitoko Murakami,' visits the ramen shop 'Satsumakko' for the first time in a while. So he hears from 'Murakami Tadashi' and 'Murakami Yoshie' that 'Chahhan' is out of order recently.<br />Ryo heads to the lesson studio for 'Chahhan'. Three people are surprised at the sudden visit of Ryo. Ryo enthusiastically scolds Yuki, Shiori, and Hitoko. Yuki is touched by Ryo's thoughts, and Shiori and Hitoko. Yuki goes to see the boy Ryo and she promises that she will definitely show success with 'pray'.<br />Three people who are making good progress toward their debut. Meanwhile, the color of the sky is changing more and more. The day when Ryo returns to the future is steadily approaching. 'Chahhan' invites Ryo to a one-man live.</p>NaNhttps://api.tvmaze.com/episodes/231102061530https://www.tvmaze.com/shows/61530/toki-wo-kakeru-bandoToki wo Kakeru BandoScriptedJapanese[Comedy, Music, Science-Fiction]Ended27.026.02020-10-202020-12-22https://www.fujitv.co.jp/tokikake/00:25[Tuesday]NaN1NaN119.0FODNaNNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/403/1009836.jpghttps://static.tvmaze.com/uploads/images/original_untouched/403/1009836.jpg<p>A story about Ryo, a mysterious and self-proclaimed music producer from the future, producing a girl band of three girls and leading them to stardom. A comical and tempo conversational drama, and various trials to produce the youth of young people who play music with comedy touch.</p>1649705311https://api.tvmaze.com/shows/61530https://api.tvmaze.com/episodes/2311020https://static.tvmaze.com/uploads/images/medium_landscape/403/1009868.jpghttps://static.tvmaze.com/uploads/images/original_untouched/403/1009868.jpg1354.0Fuji TV TWOJapanJPAsia/TokyoNaNJapanJPAsia/TokyoNaNNaNNaNJapanJPAsia/Tokyo
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872015890https://www.tvmaze.com/episodes/2015890/edgar-1x07-vos-paupieres-sont-lourdesVos paupières sont lourdes17.0regular2020-12-222020-12-22T16:00:00+00:0044.0NaN<p>The suspects swear they have no memory of the crime committed. Edgar will find their only point in common: Zéphir, the hypnotist.</p>NaNhttps://api.tvmaze.com/episodes/201589053114https://www.tvmaze.com/shows/53114/edgarEdgarScriptedFrench[Comedy, Crime, Mystery]RunningNaN42.02020-08-05Nonehttps://www.crave.ca/en/tv-shows/edgar[]NaN19NaN109.0CraveTVNaNNoneNaNNaN386521.0tt12873702https://static.tvmaze.com/uploads/images/medium_portrait/294/735665.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/735665.jpg<p>Although Edgar Aquin can go unnoticed by his appearance, he is a formidable investigator, with an extraordinary sense of observation. With his unconventional methods, sharp instincts and unique logic, he will succeed in proving the guilt of the suspects every time!</p>1611613354https://api.tvmaze.com/shows/53114https://api.tvmaze.com/episodes/2015891NaNNaNNaNNaNNaNNaNNaNNaNCanadaCAAmerica/HalifaxNaNNaNNaNNaNNaNNaN
882015891https://www.tvmaze.com/episodes/2015891/edgar-1x08-coup-de-theatreCoup de théâtre18.0regular2020-12-222020-12-22T16:00:00+00:0043.0NaN<p>Gnawed by jealousy, the actress Béatrice Rose develops a masterful plan that will sign the last act of her rival, Marie Sainclair.</p>NaNhttps://api.tvmaze.com/episodes/201589153114https://www.tvmaze.com/shows/53114/edgarEdgarScriptedFrench[Comedy, Crime, Mystery]RunningNaN42.02020-08-05Nonehttps://www.crave.ca/en/tv-shows/edgar[]NaN19NaN109.0CraveTVNaNNoneNaNNaN386521.0tt12873702https://static.tvmaze.com/uploads/images/medium_portrait/294/735665.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/735665.jpg<p>Although Edgar Aquin can go unnoticed by his appearance, he is a formidable investigator, with an extraordinary sense of observation. With his unconventional methods, sharp instincts and unique logic, he will succeed in proving the guilt of the suspects every time!</p>1611613354https://api.tvmaze.com/shows/53114https://api.tvmaze.com/episodes/2015891NaNNaNNaNNaNNaNNaNNaNNaNCanadaCAAmerica/HalifaxNaNNaNNaNNaNNaNNaN
892165008https://www.tvmaze.com/episodes/2165008/all-about-android-2020-12-22-best-of-2020Best of 2020202051.0regular2020-12-222020-12-22T17:00:00+00:0090.0NaNNoneNaNhttps://api.tvmaze.com/episodes/216500817633https://www.tvmaze.com/shows/17633/all-about-androidAll About AndroidNewsEnglish[]RunningNaN90.02011-03-29Nonehttps://twit.tv/shows/all-about-android[Tuesday]NaN44NaN102.0TwitNaNNoneNaNNaN260436.0tt3589312https://static.tvmaze.com/uploads/images/medium_portrait/59/148354.jpghttps://static.tvmaze.com/uploads/images/original_untouched/59/148354.jpg<p><b>All About Android </b>delivers everything you want to know about Android each week -- the biggest news, freshest hardware, best apps and geekiest how-to's -- with Android enthusiasts Jason Howell, Florence Ion, Ron Richards, and a variety of special guests along the way.</p>1653765273https://api.tvmaze.com/shows/17633https://api.tvmaze.com/episodes/2335726NaNNaNNaNNaNNaNNaNNaNNaNUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaN
901968003https://www.tvmaze.com/episodes/1968003/a-teacher-1x09-episode-9Episode 919.0regular2020-12-222020-12-22T17:00:00+00:0030.0NaN<p>Claire and Eric separately hit their breaking points.</p>7.7https://api.tvmaze.com/episodes/196800338339https://www.tvmaze.com/shows/38339/a-teacherA TeacherScriptedEnglish[Drama]EndedNaN27.02020-11-102020-12-29https://www.hulu.com/series/a-teacher-1c871218-05b1-4c66-a22f-260b2cb9bbf9[Tuesday]5.894NaN2.0HuluNaNhttps://www.hulu.com/NaNNaN352440.0tt10680614https://static.tvmaze.com/uploads/images/medium_portrait/272/681431.jpghttps://static.tvmaze.com/uploads/images/original_untouched/272/681431.jpg<p><b>A Teacher</b> examines the complexities and consequences of an illegal relationship between a female teacher, Claire and her male high school student, Eric. Dissatisfied in their own lives, Claire and Eric discover an undeniable escape in each other, but their relationship accelerates faster than anticipated and the permanent damage becomes impossible to ignore.</p>1637344861https://api.tvmaze.com/shows/38339https://api.tvmaze.com/episodes/1968004https://static.tvmaze.com/uploads/images/medium_landscape/289/724613.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/724613.jpgNaNNaNNaNNaNNaNNaNUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaN
911991991https://www.tvmaze.com/episodes/1991991/reverse-engineering-2020-12-22-recreating-marcus-samuelssons-swedish-meatballs-from-tasteRecreating Marcus Samuelsson's Swedish Meatballs From Taste20205.0regular2020-12-222020-12-22T17:00:00+00:0024.0NaN<p>We challenged resident Bon Appétit super taster Chris Morocco to recreate Marcus Samuelsson's Swedish meatballs using every sense he has other than sight. Was he up to the challenge?</p>NaNhttps://api.tvmaze.com/episodes/199199145512https://www.tvmaze.com/shows/45512/reverse-engineeringReverse EngineeringRealityEnglish[Food]RunningNaN27.02019-05-28Nonehttps://video.bonappetit.com/series/reverse-engineering[]NaN27NaN303.0bon appétit videoNaNNoneNaNNaN370135.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/242/606483.jpghttps://static.tvmaze.com/uploads/images/original_untouched/242/606483.jpg<p>One dish. Two days. A challenge for super taster Chris Morocco to blindly taste a dish made by a famous chef and then reverse engineer it as closely to the original as he can.</p>1661528841https://api.tvmaze.com/shows/45512https://api.tvmaze.com/episodes/2380681https://static.tvmaze.com/uploads/images/medium_landscape/414/1037293.jpghttps://static.tvmaze.com/uploads/images/original_untouched/414/1037293.jpgNaNNaNNaNNaNNaNNaNUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaN
922380808https://www.tvmaze.com/episodes/2380808/dimension-20s-adventuring-party-3x05-the-person-among-muppetsThe Person Among Muppets35.0regular2020-12-222020-12-22T17:00:00+00:0057.0NaNNoneNaNhttps://api.tvmaze.com/episodes/238080863761https://www.tvmaze.com/shows/63761/dimension-20s-adventuring-partyDimension 20's Adventuring PartyTalk ShowEnglish[]Running57.057.02020-04-08NoneNone[]NaN7NaN311.0DropoutNaNNoneNaNNaN391568.0tt13280542https://static.tvmaze.com/uploads/images/medium_portrait/420/1050072.jpghttps://static.tvmaze.com/uploads/images/original_untouched/420/1050072.jpg<p>Adventuring Party is a series of livestreamed talk-back episodes that aired after each new episode of A Crown of Candy. An additional episode was pre-recorded featuring the Pirates of Leviathan following the release of episode 4. Each Adventuring Party episode features the Dimension 20 cast as they talk about the events of the most recent episode, their experiences during that session, any unique challenges or situations they encountered, and answer as many fan questions as Brennan allows.</p><p><br /> </p>1661532809https://api.tvmaze.com/shows/63761https://api.tvmaze.com/episodes/2380882NaNNaNNaNNaNNaNNaNNaNNaNUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaN
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